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687 articles · Page 7 of 7
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 12, 2019 · Artificial Intelligence

How AI and RFID Combine to Track Customer‑Product Interactions in Retail

This article presents a comprehensive AI‑driven framework that fuses video‑based customer action detection, RFID‑based product flip detection, and bipartite graph matching to accurately determine when, where, and which customer interacts with which SKU in a retail environment, discussing algorithms, optimizations, and experimental results.

AICustomer BehaviorRFID
0 likes · 22 min read
How AI and RFID Combine to Track Customer‑Product Interactions in Retail
JD Tech
JD Tech
Mar 8, 2019 · Artificial Intelligence

Integrated Engineering & Algorithm Platform for AI Visual Applications

This article describes a comprehensive, end‑to‑end AI visual algorithm platform that unifies data collection, annotation, model training, deployment, testing, quality evaluation, and service gateways, illustrating how such integration improves transparency, efficiency, and quality across use cases like background removal, face swapping, and clothing recommendation.

AIAlgorithm PlatformClothing Recommendation
0 likes · 13 min read
Integrated Engineering & Algorithm Platform for AI Visual Applications
Hulu Beijing
Hulu Beijing
Mar 7, 2019 · Artificial Intelligence

From AlexNet to ResNeXt: Key Milestones in CNN Evolution

This article traces the evolution of convolutional neural networks from the pioneering AlexNet through VGG, Inception, ResNet, Inception‑v4, Inception‑ResNet and ResNeXt, highlighting architectural innovations, performance gains, and the underlying biological inspirations that shaped modern deep learning models.

AlexNetCNNInception
0 likes · 13 min read
From AlexNet to ResNeXt: Key Milestones in CNN Evolution
21CTO
21CTO
Mar 4, 2019 · Artificial Intelligence

How to Spot AI‑Generated Fake Faces: Tips, Tricks, and the Tech Behind StyleGAN

This article explains why AI‑generated faces from StyleGAN are hard to distinguish, introduces an online game for testing realism, and provides practical visual cues—such as water spots, background errors, asymmetric glasses, hair artifacts, and teeth anomalies—to reliably identify fake images.

AI-generated imagesGaNStyleGAN
0 likes · 8 min read
How to Spot AI‑Generated Fake Faces: Tips, Tricks, and the Tech Behind StyleGAN
Ctrip Technology
Ctrip Technology
Feb 28, 2019 · Artificial Intelligence

OCR Techniques and Solutions for Ctrip Business: Deep Learning Based Text Detection and Recognition

This article presents an overview of computer‑vision based OCR in Ctrip's operations, detailing deep‑learning text detection methods for controlled and uncontrolled scenarios, sequence‑based recognition models, training strategies with synthetic data, and performance results, while discussing current challenges and future improvements.

AICtripOCR
0 likes · 11 min read
OCR Techniques and Solutions for Ctrip Business: Deep Learning Based Text Detection and Recognition
Xianyu Technology
Xianyu Technology
Feb 27, 2019 · Artificial Intelligence

UI2CODE: Layout Analysis and Background/Foreground Extraction for UI Images

The UI2CODE system tackles UI layout analysis by first extracting backgrounds with Sobel, Laplacian and Canny edge detection plus a flood‑fill algorithm, then isolating foreground components through connected‑component analysis and a Faster R‑CNN classifier, and finally fusing both pipelines to achieve superior precision, recall and IoU on Xianyu app screenshots.

Faster R-CNNUI2Codecomputer vision
0 likes · 16 min read
UI2CODE: Layout Analysis and Background/Foreground Extraction for UI Images
System Architect Go
System Architect Go
Feb 26, 2019 · Fundamentals

Master the Basics of Image Processing with OpenCV and NumPy

This article introduces core image processing concepts—pixel fundamentals, binary, grayscale, and RGB images, matrix representation—and demonstrates practical implementations of cropping, canvas creation, watermarking, translation, rotation, and scaling using Python's OpenCV and NumPy libraries, including algorithm choices for resizing.

NumPyOpenCVPython
0 likes · 5 min read
Master the Basics of Image Processing with OpenCV and NumPy
ITPUB
ITPUB
Feb 23, 2019 · Artificial Intelligence

Explore a 1.59 Million Image NSFW Dataset with 159 Fine-Grained Categories

A data scientist from Besedo has open‑sourced a massive NSFW image dataset containing 1.589 million pictures, organized into 159 primary categories and further sub‑categories, with download scripts and GitHub links, requiring about 500 GB of storage and cautioning against viewing in the office.

AI researchGitHubLarge Dataset
0 likes · 3 min read
Explore a 1.59 Million Image NSFW Dataset with 159 Fine-Grained Categories
21CTO
21CTO
Feb 22, 2019 · Fundamentals

Why the Iconic “Lenna” Photo Became the Face of Image‑Processing Research

The article recounts how a 1960 Playboy portrait of Lena Söderberg was adopted by image‑processing researchers as a standard test image, explains the technical and cultural reasons for its lasting popularity, and follows her unexpected rise to fame within the scientific community.

Lennabenchmarkcompression
0 likes · 7 min read
Why the Iconic “Lenna” Photo Became the Face of Image‑Processing Research
ITPUB
ITPUB
Feb 16, 2019 · Artificial Intelligence

A 1.59 Million‑Image NSFW Dataset Released for Advanced Content Filtering

Data scientist Evgeny Bazarov has open‑sourced a 1.589 million‑image NSFW dataset organized into 159 fine‑grained categories, providing GitHub links, download scripts, and a 500 GB storage requirement, enabling researchers to build more precise adult‑content detection models.

GitHubLarge DatasetNSFW dataset
0 likes · 3 min read
A 1.59 Million‑Image NSFW Dataset Released for Advanced Content Filtering
Alibaba Cloud Developer
Alibaba Cloud Developer
Feb 12, 2019 · Artificial Intelligence

Essential AI Research Highlights to Jump‑Start Your Post‑Holiday Learning

After the Chinese New Year break, this curated collection of key AI articles—spanning computer vision, speech recognition, natural language processing, recommendation systems, and more—helps technical readers quickly regain momentum in work and study by revisiting core technologies with real‑world case studies.

AIcomputer visionspeech recognition
0 likes · 6 min read
Essential AI Research Highlights to Jump‑Start Your Post‑Holiday Learning
21CTO
21CTO
Feb 7, 2019 · Artificial Intelligence

How to Build a Real‑Time Parking Spot Detector with Mask R‑CNN and Python

This tutorial walks through using a webcam, Mask R‑CNN, and Python to automatically detect available parking spaces, track stationary vehicles, compute Intersection‑over‑Union to confirm emptiness, and send SMS alerts via Twilio, providing full code snippets and practical tips.

IoUMask R-CNNPython
0 likes · 16 min read
How to Build a Real‑Time Parking Spot Detector with Mask R‑CNN and Python
JD Tech
JD Tech
Jan 30, 2019 · Artificial Intelligence

JD AI Presents Eight Papers at AAAI 2019 Showcasing Advances in Machine Learning, NLP, and Computer Vision

At AAAI 2019 in Hawaii, JD AI Research Institute had eight papers accepted covering machine learning, natural language processing, computer vision, and multimodal AI, highlighting innovations such as AutoZOOM black‑box attacks, SACN for knowledge base completion, and temporally aware video captioning models.

Artificial Intelligencecomputer visionmultimodal learning
0 likes · 11 min read
JD AI Presents Eight Papers at AAAI 2019 Showcasing Advances in Machine Learning, NLP, and Computer Vision
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 29, 2019 · Artificial Intelligence

Alibaba's AI-Driven In-Store Foot Traffic Digitization

Alibaba’s search division showcases how AI transforms traditional retail by digitizing in‑store foot traffic, employing camera‑based person detection, re‑identification, RFID‑enhanced product interaction, and edge‑optimized models to generate real‑time customer insights, heatmaps, and personalized recommendations that bridge offline and online shopping experiences.

AIRFIDcomputer vision
0 likes · 25 min read
Alibaba's AI-Driven In-Store Foot Traffic Digitization
ITPUB
ITPUB
Jan 27, 2019 · Artificial Intelligence

Achieve 99% Accurate Face Recognition with Python’s face_recognition Library

This guide introduces the open‑source Python library face_recognition, explains its high‑accuracy (up to 99.38%) facial detection and landmark capabilities, provides step‑by‑step code examples for locating faces, extracting landmarks, and comparing identities, and lists practical use‑case scenarios and the GitHub repository.

GitHubPythoncomputer vision
0 likes · 6 min read
Achieve 99% Accurate Face Recognition with Python’s face_recognition Library
DataFunTalk
DataFunTalk
Jan 14, 2019 · Artificial Intelligence

Computer Vision Fundamentals, Traditional Methods, Deep Learning Advances, and Cloud AI Deployment

This article provides a comprehensive overview of computer vision, covering its basic concepts, traditional image processing techniques, modern deep‑learning approaches, real‑world AI application cases, and the cloud infrastructure needed to support large‑scale deployment, while also offering skill‑advancement guidance.

AI Applicationscloud AIcomputer vision
0 likes · 20 min read
Computer Vision Fundamentals, Traditional Methods, Deep Learning Advances, and Cloud AI Deployment
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 8, 2019 · Artificial Intelligence

How Alibaba Digitizes In‑Store Foot Traffic with AI and RFID Fusion

This article details Alibaba's end‑to‑end solution for digitizing offline retail foot traffic, combining existing surveillance cameras, RFID tags, and advanced AI techniques such as lightweight YOLO detection, knowledge distillation, and multi‑level pedestrian re‑identification to capture, analyze, and act on shopper behavior for both business operations and personalized in‑store experiences.

AIEdge computingPedestrian Re-identification
0 likes · 27 min read
How Alibaba Digitizes In‑Store Foot Traffic with AI and RFID Fusion
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 7, 2019 · Artificial Intelligence

What Are Alibaba DAMO Academy’s 2019 Top 10 Tech Trends and Their Real-World Impact?

This week’s Alibaba tech roundup highlights the DAMO Academy’s 2019 top‑10 technology trends—from smart cities and AI chips to blockchain and 5G—plus breakthrough AI liver‑tumor segmentation results, the open‑source Fusion design system, a Flink Forward China recap, a new computer‑vision paper collection, and an upcoming Apache Dubbo live session.

computer visionopen-source
0 likes · 9 min read
What Are Alibaba DAMO Academy’s 2019 Top 10 Tech Trends and Their Real-World Impact?
DataFunTalk
DataFunTalk
Dec 20, 2018 · Artificial Intelligence

How to Build World-Class Visual AI Technology

This presentation outlines the fundamentals of computer vision, discusses key factors such as algorithm research, large‑scale training platforms, intelligent data processing, and hardware optimization, and shares practical experiences from DeepGlint on building a world‑class visual AI system and its real‑world applications.

Data Pipelinecomputer visionhardware optimization
0 likes · 23 min read
How to Build World-Class Visual AI Technology
Tencent Cloud Developer
Tencent Cloud Developer
Dec 17, 2018 · Artificial Intelligence

An Overview of Computer Vision: Fundamentals, Traditional Techniques, and Deep Learning Applications

The talk provides a comprehensive overview of computer vision, defining its scope, detailing low‑, mid‑, and high‑level processing pipelines, reviewing classic filters and feature extractors, explaining deep‑learning breakthroughs such as CNNs and YOLO, and showcasing Tencent Cloud AI services, career paths, and learning resources.

AIcomputer visionmachine learning
0 likes · 43 min read
An Overview of Computer Vision: Fundamentals, Traditional Techniques, and Deep Learning Applications
360 Quality & Efficiency
360 Quality & Efficiency
Dec 7, 2018 · Artificial Intelligence

Image Feature Extraction and Clustering for Key Frame Selection in Mobile App Installation Screenshots

This article presents a technical solution for extracting representative key frames from time‑series screenshots of a mobile app installation process, covering pixel sampling, dimensionality reduction, classic feature extractors (SIFT, HOG, ORB), auto‑encoder based deep learning, and clustering methods such as KMeans and DBSCAN, along with practical results and performance analysis.

AutoencoderClusteringHOG
0 likes · 5 min read
Image Feature Extraction and Clustering for Key Frame Selection in Mobile App Installation Screenshots
Tencent Cloud Developer
Tencent Cloud Developer
Dec 5, 2018 · Artificial Intelligence

19 AI Technologies That Are Currently Dominating

The article surveys the nineteen leading AI technologies—from natural language generation and speech recognition to digital twins and marketing automation—detailing their core functions, common use cases such as customer service, security, content creation, and the key vendors delivering each solution.

AI TechnologiesArtificial Intelligencecomputer vision
0 likes · 17 min read
19 AI Technologies That Are Currently Dominating
21CTO
21CTO
Nov 21, 2018 · Artificial Intelligence

What’s Driving the Rapid Evolution of Face Recognition Technology?

This comprehensive overview examines the fundamentals, historical milestones, key algorithms, major datasets, policy support, industry applications, and future trends of face recognition technology, highlighting its rapid growth within computer vision and artificial intelligence.

AIBiometricscomputer vision
0 likes · 45 min read
What’s Driving the Rapid Evolution of Face Recognition Technology?
Xianyu Technology
Xianyu Technology
Nov 20, 2018 · Artificial Intelligence

How to Separate Complex Image Foreground from Background Using AI and Classic CV Techniques

This article presents a step‑by‑step solution that combines computer‑vision preprocessing, OCR, CNN classification, shape matching, and inpainting to isolate meaningful foreground elements from images with intricate backgrounds, discussing practical results, limitations, and code implementations.

OpenCVTensorFlowcomputer vision
0 likes · 15 min read
How to Separate Complex Image Foreground from Background Using AI and Classic CV Techniques
MaGe Linux Operations
MaGe Linux Operations
Nov 16, 2018 · Artificial Intelligence

Real-Time Object Detection with OpenCV, Python, and Deep Learning

This tutorial walks through extending a deep‑learning object detector to process live video streams using OpenCV and Python, covering setup, command‑line arguments, model loading, frame‑by‑frame detection, drawing bounding boxes, FPS measurement, and performance tips.

Video Streamcomputer visionobject detection
0 likes · 9 min read
Real-Time Object Detection with OpenCV, Python, and Deep Learning
Alibaba Cloud Developer
Alibaba Cloud Developer
Oct 19, 2018 · Artificial Intelligence

How Alibaba’s AI‑Powered “Future Store” Redefines Unmanned Retail

Alibaba’s senior tech expert explains the concept, architecture, core AI capabilities, real‑world case studies, and future roadmap of the Tmall “Future Store”, a vision‑driven, sensor‑rich unmanned retail experience that merges computer‑vision, edge computing, and data‑driven operations.

AIAlibabaEdge computing
0 likes · 17 min read
How Alibaba’s AI‑Powered “Future Store” Redefines Unmanned Retail
Tencent Cloud Developer
Tencent Cloud Developer
Oct 12, 2018 · Artificial Intelligence

Understanding Convolutional Neural Networks (CNN) with Keras

The article introduces convolutional neural networks, explains core concepts such as convolution, padding, stride, and pooling, demonstrates how to calculate output dimensions, and provides a step‑by‑step Keras example that builds, compiles, and trains a multi‑layer CNN for image classification.

CNNKerasPython
0 likes · 8 min read
Understanding Convolutional Neural Networks (CNN) with Keras
Architects Research Society
Architects Research Society
Oct 7, 2018 · Artificial Intelligence

The Rise of Deep Neural Networks: From Research Breakthroughs to Industry Adoption

Deep neural networks, propelled by breakthroughs such as AlexNet and advances in GPU and TPU hardware, are rapidly moving from academic research into diverse applications—including earthquake prediction, medical imaging, and autonomous driving—driving massive industry investment, new semiconductor designs, and intense competition among tech giants and startups.

AI hardwareGPUTPU
0 likes · 9 min read
The Rise of Deep Neural Networks: From Research Breakthroughs to Industry Adoption
21CTO
21CTO
Sep 14, 2018 · Artificial Intelligence

From Stanford to Google: How Fei‑Fei Li Built ImageNet and Shaped AI

Fei‑Fei Li, the pioneering AI researcher and former Google Cloud AI lead, rose from humble beginnings in China to create the ImageNet dataset, drive breakthroughs in computer vision, and now returns to Stanford, illustrating how curiosity and perseverance can transform both academia and industry.

Artificial IntelligenceFei-Fei LiGoogle AI
0 likes · 12 min read
From Stanford to Google: How Fei‑Fei Li Built ImageNet and Shaped AI
Qunar Tech Salon
Qunar Tech Salon
Sep 11, 2018 · Artificial Intelligence

Overview of Deep Learning Object Detection Methods and Detailed Implementation of Faster R‑CNN

This article reviews major deep‑learning object detection approaches—including one‑stage YOLO and SSD and two‑stage RCNN, Fast RCNN, and Faster RCNN—then provides a step‑by‑step explanation of Faster RCNN’s architecture, region‑proposal network, RoI pooling, loss functions, and sample PyTorch code.

Faster R-CNNPyTorchPython
0 likes · 20 min read
Overview of Deep Learning Object Detection Methods and Detailed Implementation of Faster R‑CNN
JavaScript
JavaScript
Sep 8, 2018 · Artificial Intelligence

How Sketch2Code Turns Hand‑Drawn UI Designs into Ready‑to‑Use HTML with AI

Sketch2Code leverages Microsoft’s custom vision model, OCR, and Azure services to automatically convert hand‑drawn UI mockups into functional HTML code, detailing its workflow—from image upload and element prediction to layout generation and final HTML output—plus links to the repository and demo site.

AIAzureHTML generation
0 likes · 3 min read
How Sketch2Code Turns Hand‑Drawn UI Designs into Ready‑to‑Use HTML with AI
MaGe Linux Operations
MaGe Linux Operations
Aug 21, 2018 · Artificial Intelligence

How Deep Learning Transformed Face Recognition: From Images to Real‑Time Video

This article surveys the evolution of face recognition from early statistical methods to modern deep‑learning approaches, outlines key researchers, open‑source projects, popular APIs, core processing steps, the DeepFace architecture, datasets, and experimental results, providing a comprehensive guide for practitioners and researchers.

CNNOpenCVcomputer vision
0 likes · 22 min read
How Deep Learning Transformed Face Recognition: From Images to Real‑Time Video
iQIYI Technical Product Team
iQIYI Technical Product Team
Aug 10, 2018 · Artificial Intelligence

iQIYI Releases World's First Multimodal, Multi-angle Celebrity Video Dataset (iQIYI-VID) and Announces AI Competition

iQIYI released iQIYI-VID, the world’s first multimodal, multi-angle celebrity video dataset (1,000 hours, 500,000 clips, 5,000 celebrities) for a new AI competition focusing on multimodal video person recognition, which has attracted global university teams and top computer‑vision judges to advance AI understanding in entertainment.

AI datasetCompetitioncomputer vision
0 likes · 7 min read
iQIYI Releases World's First Multimodal, Multi-angle Celebrity Video Dataset (iQIYI-VID) and Announces AI Competition
HomeTech
HomeTech
Aug 7, 2018 · Artificial Intelligence

Overview of Object Detection Algorithms: Two‑Stage and One‑Stage Methods

This article reviews the evolution of visual object detection, explaining traditional region‑based approaches, the rise of deep‑learning two‑stage frameworks such as R‑CNN, Fast R‑CNN and Faster R‑CNN, and the faster one‑stage models like Overfeat, YOLO, SSD and RetinaNet, together with their design choices, training strategies and loss functions.

R-CNNSSDYOLO
0 likes · 17 min read
Overview of Object Detection Algorithms: Two‑Stage and One‑Stage Methods
Tencent Cloud Developer
Tencent Cloud Developer
Aug 6, 2018 · Artificial Intelligence

Tencent's AI Breast Cancer Screening System: Technical Architecture and Implementation

Tencent's AI Breast System combines mammography, pathology, MRI and ultrasound analysis using a multi‑scale, progressive TMuNet model that processes four views, learns from physician feedback, and delivers lesion localization, malignancy scoring and automated reports, achieving up to 92% sensitivity and reducing annotation time.

AI Medical ImagingBreast Cancer DetectionHealthcare AI
0 likes · 13 min read
Tencent's AI Breast Cancer Screening System: Technical Architecture and Implementation
Tencent Cloud Developer
Tencent Cloud Developer
Aug 1, 2018 · Artificial Intelligence

How AI Powers Real-World Apps: From Face Filters to Medical Imaging

The July 28 Tencent Cloud community salon in Beijing gathered five AI experts who demonstrated practical AI applications—including computer‑vision face filters, OCR services, smart construction attendance, game AI, and breast‑cancer detection—showing how cloud‑based models, data pipelines, and deployment strategies turn research into usable products.

AIIndustry ApplicationsOCR
0 likes · 21 min read
How AI Powers Real-World Apps: From Face Filters to Medical Imaging
Qunar Tech Salon
Qunar Tech Salon
Jul 24, 2018 · Artificial Intelligence

Meituan's AI-Powered Image Intelligent Review System: Watermark Detection, Celebrity Face Recognition, Pornography Detection, and Scene Classification

This article describes Meituan's large‑scale AI‑driven image moderation platform, detailing deep‑learning based watermark detection, celebrity face recognition, pornographic image detection, and scene classification techniques, along with system architecture, data preparation, model evaluation, and deployment considerations.

Image Moderationcomputer visiondeep learning
0 likes · 19 min read
Meituan's AI-Powered Image Intelligent Review System: Watermark Detection, Celebrity Face Recognition, Pornography Detection, and Scene Classification
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 6, 2018 · Artificial Intelligence

How Dynamic Scale Selection Boosts Real-Time Action Prediction

This article explains online action prediction, the challenges of early‑stage classification, and introduces a Scale Selection Network that dynamically chooses optimal temporal windows using dilated convolutions, regression and classification sub‑networks, achieving state‑of‑the‑art results on two benchmark datasets.

computer visiondeep learningdilated convolution
0 likes · 7 min read
How Dynamic Scale Selection Boosts Real-Time Action Prediction
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 4, 2018 · Artificial Intelligence

Turning Fashion Into AI‑Ready Data: Building Practical Image Datasets

This article explains how Alibaba's Image & Beauty team designs and iterates a practical fashion image dataset by aligning data purpose, integrating professional knowledge, handling sample scarcity and structured noise, and defining fine‑grained evaluation metrics to enable AI models that truly understand clothing.

Knowledge engineeringcomputer visiondata annotation
0 likes · 34 min read
Turning Fashion Into AI‑Ready Data: Building Practical Image Datasets
Xianyu Technology
Xianyu Technology
Jun 30, 2018 · Artificial Intelligence

No-Reference Image Sharpness Assessment Based on Strong Edge Validity Statistics

The paper proposes a no‑reference image sharpness metric that computes strong‑edge validity statistics—ratio of maximum directional gradient sum to squared strong‑edge count—across image blocks, classifies them into grades, and effectively handles defocus and motion blur for applications such as video thumbnail selection.

No-Referencecomputer visionedge statistics
0 likes · 8 min read
No-Reference Image Sharpness Assessment Based on Strong Edge Validity Statistics
MaGe Linux Operations
MaGe Linux Operations
Jun 29, 2018 · Artificial Intelligence

How to Build a 200-Line Python Script for Automatic Face Swapping

This article walks through creating a concise 200‑line Python script that automatically detects facial landmarks with dlib, aligns faces using Procrustes analysis, corrects color differences, and blends a second face onto a first image, complete with code snippets and step‑by‑step explanations.

OpenCVcomputer visiondlib
0 likes · 9 min read
How to Build a 200-Line Python Script for Automatic Face Swapping
Qunar Tech Salon
Qunar Tech Salon
Jun 29, 2018 · Artificial Intelligence

Face Recognition with OpenCV, Python, and Deep Learning

This tutorial explains how to implement high‑accuracy face recognition using OpenCV, Python, and deep learning by leveraging dlib's deep metric learning, creating a custom dataset, encoding facial embeddings, and performing real‑time identification on images and video streams.

OpenCVPythoncomputer vision
0 likes · 30 min read
Face Recognition with OpenCV, Python, and Deep Learning
Meituan Technology Team
Meituan Technology Team
Jun 28, 2018 · Artificial Intelligence

Deep Learning-Based OCR Techniques at Meituan

Meituan’s OCR system replaces the classic preprocess‑segment‑recognize pipeline with deep‑learning components—CNN‑based text detection, synthetic‑data‑trained character models, and BLSTM‑CTC sequence recognition—delivering far higher accuracy on noisy, varied real‑world images such as menus, receipts, and IDs, though further integration with layout analysis remains needed.

OCRSequence Learningcomputer vision
0 likes · 22 min read
Deep Learning-Based OCR Techniques at Meituan
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 27, 2018 · Artificial Intelligence

How Context-Contrast Features and Gated Multi‑Scale Fusion Boost Scene Segmentation

The paper introduces a context‑contrast local feature and a gated multi‑scale fusion mechanism that together enhance pixel‑level scene segmentation, especially for inconspicuous objects, and validates the approach with state‑of‑the‑art results on Pascal Context, SUN‑RGBD, and COCO Stuff datasets.

computer visioncontext contrastdeep learning
0 likes · 6 min read
How Context-Contrast Features and Gated Multi‑Scale Fusion Boost Scene Segmentation
Tencent Cloud Developer
Tencent Cloud Developer
Jun 8, 2018 · Industry Insights

How AI and Data Are Powering the Next Retail Revolution with Tencent Cloud

The article analyzes the challenges of declining online traffic and low in‑store conversion, then details how Tencent Cloud’s AI‑driven retail suite—covering scientific site selection, commercial‑area insights, computer‑vision store management, one‑code product tracking, and brand sentiment analysis—offers data‑powered solutions for modern retailers.

AICloud ComputingIndustry Insights
0 likes · 12 min read
How AI and Data Are Powering the Next Retail Revolution with Tencent Cloud
AntTech
AntTech
Jun 1, 2018 · Mobile Development

Optimizing QR Code Scanning: Boosting Recognition Rate, Cutting Latency, and Enhancing Robustness

This article details how Alipay's scanning technology team improved QR code recognition by refining aspect‑ratio tolerance, introducing new pattern detection modes, applying diagonal filtering, leveraging logistic‑regression classification, adjusting jump‑line intervals, and moving binarization to GPU, resulting in a 6.95‑point increase in recognition rate and significantly reduced processing time.

QR codealgorithm optimizationcomputer vision
0 likes · 12 min read
Optimizing QR Code Scanning: Boosting Recognition Rate, Cutting Latency, and Enhancing Robustness
Architecture Digest
Architecture Digest
May 19, 2018 · Artificial Intelligence

Optical Flow: Principles, Evolution, and Applications in Computer Vision

This article explains the fundamentals of optical flow, traces its development from early variational methods to modern deep‑learning models like FlowNet, and discusses practical applications such as video object detection, semantic segmentation, and novel view synthesis, highlighting both technical challenges and future research directions.

FlowNetLucas-Kanadecomputer vision
0 likes · 14 min read
Optical Flow: Principles, Evolution, and Applications in Computer Vision
360 Tech Engineering
360 Tech Engineering
May 17, 2018 · Artificial Intelligence

Applying Image Recognition in UI Automation Testing with Sikuli

This article introduces how image‑recognition techniques, particularly using the Sikuli tool, can be applied to UI automation testing for both web and mobile applications, covering practical scenarios, core principles, a suite of useful functions, example code, and the advantages and limitations of the approach.

SikuliUI automationcomputer vision
0 likes · 7 min read
Applying Image Recognition in UI Automation Testing with Sikuli
360 Quality & Efficiency
360 Quality & Efficiency
May 16, 2018 · Fundamentals

Applying Image Recognition in UI Automation Testing with Sikuli

This article introduces the use of image‑recognition techniques, particularly the Sikuli tool, for UI automation testing, covering typical scenarios, underlying principles, key functions such as Find, click, wait, and type, as well as example code, and discusses the advantages and limitations of this approach.

JythonSikuliUI automation
0 likes · 7 min read
Applying Image Recognition in UI Automation Testing with Sikuli
Ctrip Technology
Ctrip Technology
May 2, 2018 · Artificial Intelligence

Document OCR: From Computer Vision Fundamentals to Ctrip's Full-Text OCR Implementation

This article explains the evolution of optical character recognition, outlines the complete OCR processing pipeline—including image input, preprocessing, binarization, noise removal, tilt correction, layout analysis, character segmentation, recognition, and post‑processing—while showcasing Ctrip's real‑world OCR project, its architecture, accuracy metrics, and key computer‑vision techniques such as CNN, HSV, HOG, LBP, and Haar features.

CNNOCRcomputer vision
0 likes · 13 min read
Document OCR: From Computer Vision Fundamentals to Ctrip's Full-Text OCR Implementation
MaGe Linux Operations
MaGe Linux Operations
Mar 27, 2018 · Artificial Intelligence

How to Swap Faces in Images with Python: A Step‑by‑Step Guide

This article explains how to write a compact Python script (about 200 lines) that automatically detects facial landmarks with dlib, aligns two faces using Procrustes analysis, corrects color differences, and blends the second face onto the first using OpenCV, complete with full source code and visual examples.

OpenCVPythoncomputer vision
0 likes · 13 min read
How to Swap Faces in Images with Python: A Step‑by‑Step Guide
Suning Technology
Suning Technology
Jan 26, 2018 · Artificial Intelligence

Suning’s ‘Beidou’ AI System Transforms Retail Customer Flow Analytics

The article details Suning’s Beidou system, an AI‑driven solution that combines video, WiFi and facial recognition to accurately count and analyze customer flow, improve store operations, and enable intelligent services such as personalized recommendations, automated payment, and safety monitoring for modern retail environments.

AIcomputer visionretail analytics
0 likes · 13 min read
Suning’s ‘Beidou’ AI System Transforms Retail Customer Flow Analytics
JD Tech
JD Tech
Jan 26, 2018 · Artificial Intelligence

JD Big Data R&D Department Presents Three Accepted Papers at AAAI-2018

The JD Big Data R&D team announced that three of its research papers—covering cross‑domain human parsing, multi‑view outlier detection, and orthogonal weight normalization for deep neural networks—were accepted at the prestigious AAAI‑2018 conference, highlighting the department's contributions to computer vision, data mining, and deep learning.

Artificial IntelligenceCross‑domain Adaptationcomputer vision
0 likes · 8 min read
JD Big Data R&D Department Presents Three Accepted Papers at AAAI-2018
MaGe Linux Operations
MaGe Linux Operations
Jan 21, 2018 · Artificial Intelligence

Can You Break a WordPress CAPTCHA in 15 Minutes with Machine Learning?

This tutorial shows how to generate a labeled dataset from the open‑source WordPress "Really Simple CAPTCHA" plugin, train a lightweight convolutional neural network using Python, OpenCV, Keras and TensorFlow, and decode real captchas within fifteen minutes, demonstrating the power of modern computer‑vision techniques.

TensorFlowcomputer vision
0 likes · 11 min read
Can You Break a WordPress CAPTCHA in 15 Minutes with Machine Learning?
21CTO
21CTO
Jan 6, 2018 · Artificial Intelligence

How Image Recognition Transforms Our World: Principles, Processes, and Future

This article explains the fundamentals of image recognition technology, its underlying principles, processing steps, neural‑network and nonlinear‑dimensionality‑reduction approaches, and highlights its wide‑range applications and future potential across many industries.

AIcomputer visiondimensionality reduction
0 likes · 11 min read
How Image Recognition Transforms Our World: Principles, Processes, and Future
Node Underground
Node Underground
Nov 24, 2017 · Artificial Intelligence

Build Your First Node.js Face Recognition App with opencv4nodejs

This article introduces how to leverage the opencv4nodejs Node.js module—binding OpenCV’s full API—to develop a face detection and recognition application, highlighting the CPU‑intensive nature of computer‑vision tasks, the limitations of JavaScript, and the availability of synchronous and asynchronous examples.

Node.jsOpenCVcomputer vision
0 likes · 2 min read
Build Your First Node.js Face Recognition App with opencv4nodejs
MaGe Linux Operations
MaGe Linux Operations
Nov 5, 2017 · Artificial Intelligence

How Deep Learning Transforms Modern Face Recognition: From Basics to DeepFace

This article surveys the evolution of face recognition from traditional image‑based methods to real‑time video processing, highlights key researchers and open‑source projects, explains the four‑stage pipeline, details DeepFace's deep‑learning architecture, and provides practical installation and usage instructions for Python developers.

CNNDeepFacePython
0 likes · 21 min read
How Deep Learning Transforms Modern Face Recognition: From Basics to DeepFace
MaGe Linux Operations
MaGe Linux Operations
Nov 1, 2017 · Artificial Intelligence

Master Face Recognition on Ubuntu with Python: Step‑by‑Step Guide

This guide walks through setting up Ubuntu 17.10 with Python 2.7, installing dlib and the face_recognition library, and demonstrates five practical examples ranging from a one‑line face‑recognition command to facial feature extraction and beautification, complete with code snippets and screenshots.

PythonUbuntucomputer vision
0 likes · 10 min read
Master Face Recognition on Ubuntu with Python: Step‑by‑Step Guide
Alibaba Cloud Developer
Alibaba Cloud Developer
Oct 25, 2017 · Artificial Intelligence

How Hierarchical Multimodal LSTM Boosts Image Captioning Accuracy

This article reviews an ICCV paper introducing a hierarchical multimodal LSTM that jointly embeds images, phrases, and whole sentences, enabling detailed image descriptions and superior performance on Flickr30K, MS‑COCO, and region‑phrase datasets compared to previous methods.

Image Captioningcomputer visionhierarchical LSTM
0 likes · 8 min read
How Hierarchical Multimodal LSTM Boosts Image Captioning Accuracy
21CTO
21CTO
Oct 20, 2017 · Artificial Intelligence

How Pornhub’s New AI Identifies Adult Stars in Videos

Pornhub unveiled an AI model that uses computer‑vision techniques to automatically recognize and tag over ten thousand adult performers, allowing users to search more precisely while also involving human reviewers to verify and improve the system’s accuracy.

Adult IndustryArtificial Intelligencecomputer vision
0 likes · 5 min read
How Pornhub’s New AI Identifies Adult Stars in Videos
Architecture Digest
Architecture Digest
Sep 30, 2017 · Artificial Intelligence

Overview of Prominent Deep Learning Architectures for Computer Vision

This article surveys recent progress in deep learning by presenting key computer‑vision architectures such as AlexNet, VGG, GoogleNet, ResNet, ResNeXt, RCNN, YOLO, SqueezeNet, SegNet and GANs, providing brief descriptions, their advantages, and links to original papers and Keras implementations.

Kerascomputer visiondeep learning
0 likes · 16 min read
Overview of Prominent Deep Learning Architectures for Computer Vision
Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
Sep 8, 2017 · Artificial Intelligence

Challenges and Techniques in Image Search: Facenet Model and Triplet Loss

The article discusses the evolution of image search engines, outlines key challenges such as image quality, watermarks, speed, and feature extraction, and explains how the Facenet deep‑learning model with Triplet loss can be used to generate compact image embeddings for efficient similarity search.

computer visiondeep learningfacenet
0 likes · 7 min read
Challenges and Techniques in Image Search: Facenet Model and Triplet Loss
Architecture Digest
Architecture Digest
Aug 1, 2017 · Artificial Intelligence

Comprehensive Overview of Autonomous Driving Technologies, Companies, and Industry Trends

This article provides a detailed overview of autonomous driving, covering its evolution from electric and shared vehicles, major industry players, technical definitions, SAE level classifications, core modules such as perception, localization, decision and control, key datasets like KITTI, and emerging business opportunities in the sector.

AIIndustry Trendsautonomous driving
0 likes · 19 min read
Comprehensive Overview of Autonomous Driving Technologies, Companies, and Industry Trends
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 28, 2017 · Artificial Intelligence

Inside Alibaba AI Lab: Dr. Wang Gang on Multimodal AI and Edge Computing

In an exclusive interview, Alibaba AI Lab's distinguished scientist Dr. Wang Gang discusses the lab's research on multimodal AI, edge computing, AI hardware, bio‑inspired cognition, quantum‑deep‑learning integration, and the challenges of moving from recognition to true understanding, while also outlining Alibaba's AI talent recruitment plans.

AI researchAI talent recruitmentcomputer vision
0 likes · 25 min read
Inside Alibaba AI Lab: Dr. Wang Gang on Multimodal AI and Edge Computing
MaGe Linux Operations
MaGe Linux Operations
Jul 28, 2017 · Artificial Intelligence

How to Capture GTA V Game Frames in Python with OpenCV for AI Experiments

This tutorial walks through using Python and OpenCV to capture screen images from GTA V, covering screen grabbing, converting to NumPy arrays, improving frame rates, handling key and controller input, and setting up a basic autonomous driving test environment, all without relying on pre‑existing libraries.

GTA VOpenCVPython
0 likes · 7 min read
How to Capture GTA V Game Frames in Python with OpenCV for AI Experiments
High Availability Architecture
High Availability Architecture
Jul 14, 2017 · Artificial Intelligence

Facial Emotion Recognition Using Convolutional Neural Networks: Dataset, Model Architecture, and Evaluation

This article presents a deep‑learning approach for recognizing seven basic human facial expressions using a balanced FER2013 dataset, describes the CNN architecture built with Keras and OpenCV preprocessing, reports training on AWS GPU, and analyzes validation results and visualizations.

AWS GPUCNNKeras
0 likes · 11 min read
Facial Emotion Recognition Using Convolutional Neural Networks: Dataset, Model Architecture, and Evaluation
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 5, 2017 · Artificial Intelligence

Is This the New Golden Age of Visual AI? Insights from Alibaba Cloud

The article reviews the three historic AI booms, explains why today’s cloud‑based visual intelligence represents a distinct era, outlines five key factors for successful visual AI, and showcases real‑world Alibaba Cloud applications such as product search, city‑wide monitoring, medical diagnosis, and visual advertising.

AI ApplicationsAlibaba CloudBig Data
0 likes · 18 min read
Is This the New Golden Age of Visual AI? Insights from Alibaba Cloud
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 24, 2016 · Artificial Intelligence

How Deep Learning Revives Image Search: From Sunset to Tomorrow

Image search, once limited by early CBIR techniques, has surged back thanks to deep learning, offering improved relevance, coverage, scalability, and user experience across applications like e‑commerce, shopping, entertainment, and surveillance, while integrating data, users, models, and systems to bridge the semantic gap.

Semantic Gapcomputer visiondeep learning
0 likes · 5 min read
How Deep Learning Revives Image Search: From Sunset to Tomorrow
Ctrip Technology
Ctrip Technology
Aug 12, 2016 · Artificial Intelligence

Deep Learning Meetup Recap: Applications in Travel, Advertising, NLP, Computer Vision, and Knowledge Graphs

Last month Ctrip Technology Center hosted a deep‑learning meetup featuring academic and industry experts from UCL, Fudan, Southeast University, Nanjing University, Huawei, Sogou and others, who presented real‑world applications of deep learning in travel, advertising, natural language processing, computer vision, and knowledge graphs.

AI ApplicationsAdvertisingKnowledge Graph
0 likes · 6 min read
Deep Learning Meetup Recap: Applications in Travel, Advertising, NLP, Computer Vision, and Knowledge Graphs
Qunar Tech Salon
Qunar Tech Salon
Aug 8, 2016 · Artificial Intelligence

OCR Technology Overview and Implementation Steps for Card Number Recognition

This article provides a comprehensive overview of OCR technology, explains its definition and application scenarios, and details a five‑step workflow—including target extraction, preprocessing, character localization, digit matching, and format validation—specifically illustrated with bank card number recognition.

Bank Card RecognitionMorphological OperationsOCR
0 likes · 9 min read
OCR Technology Overview and Implementation Steps for Card Number Recognition
Meiyou UED
Meiyou UED
Jul 20, 2016 · Artificial Intelligence

What Is AR? Understanding Augmented Reality Behind Pokemon Go

This article explains augmented reality (AR), compares it with virtual reality (VR), describes the technical pipeline and design challenges of AR, illustrates its unique interaction methods, and discusses current limitations and future possibilities, using Pokemon Go as a concrete example.

ARPokemon GoVR
0 likes · 7 min read
What Is AR? Understanding Augmented Reality Behind Pokemon Go
Ctrip Technology
Ctrip Technology
Jul 18, 2016 · Artificial Intelligence

Deep Learning Applications in Ctrip Travel Guide Community

This article reviews how Ctrip’s travel guide community leverages deep learning models such as CNN, LSTM, and RCNN for multilingual text analysis, image classification, video moderation, and data matching, and outlines future directions like knowledge graphs and virtual reality.

AI Applicationscomputer visionnatural language processing
0 likes · 6 min read
Deep Learning Applications in Ctrip Travel Guide Community
21CTO
21CTO
Jan 29, 2016 · Artificial Intelligence

How Mobile Image Search Powers Real-Time Shopping: Inside Pailitao’s AI Algorithm

Mobile visual search, a long‑standing dream, has evolved from early research to a production‑grade system at Pailitao, where a five‑module AI pipeline—category prediction, object detection, feature extraction, indexing, and ranking—enables billions of images to be searched instantly on mobile devices.

Retrievalcomputer visiondeep learning
0 likes · 8 min read
How Mobile Image Search Powers Real-Time Shopping: Inside Pailitao’s AI Algorithm
ITPUB
ITPUB
Jan 28, 2016 · Artificial Intelligence

Detect Your Oven’s On/Off State with Python and OpenCV

This tutorial shows how to use Python, OpenCV, and basic image‑processing techniques to automatically detect whether a kitchen oven is on by analyzing the red indicator light captured by a home camera, providing a simple safety alert system.

Home AutomationOpenCVcomputer vision
0 likes · 7 min read
Detect Your Oven’s On/Off State with Python and OpenCV
Architects Research Society
Architects Research Society
Oct 11, 2015 · Artificial Intelligence

Decision Forests for Pixel-Level Classification in Computer Vision

This article traces the evolution of computer vision from its 1960s origins, explains the challenges of image classification and semantic segmentation, and introduces pixel-level decision forest algorithms as an efficient solution for large‑scale pixel classification tasks.

Semantic Segmentationcomputer visiondecision forest
0 likes · 9 min read
Decision Forests for Pixel-Level Classification in Computer Vision
Ctrip Technology
Ctrip Technology
Jun 29, 2015 · Artificial Intelligence

Bank Card Scanning and Recognition: Extending Support for Chinese Debit Cards

This article describes a project that enhances an open‑source card‑number scanning solution to recognize 19‑digit Chinese debit cards, addressing challenges such as black‑printed fonts, light‑colored embossed fonts, background filtering, single‑character OCR, and Luhn‑based checksum verification.

AlgorithmBank Card RecognitionOCR
0 likes · 6 min read
Bank Card Scanning and Recognition: Extending Support for Chinese Debit Cards