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IT Services Circle
IT Services Circle
Apr 23, 2026 · Industry Insights

Is “120W” Just a Trademark? How Fake High‑Wattage Phone Chargers Are Angering Consumers

The article exposes how many low‑priced chargers falsely marketed as “120W” deliver only 18‑22W, lack proper safety features, and often use proprietary protocols that prevent fast charging, urging buyers to verify output specs, choose original or certified accessories, and prefer GaN technology for reliable performance.

GANconsumer safetyfast charging
0 likes · 7 min read
Is “120W” Just a Trademark? How Fake High‑Wattage Phone Chargers Are Angering Consumers
Qborfy AI
Qborfy AI
Apr 19, 2026 · Artificial Intelligence

Boosting Claude’s Front‑End Development with a GAN‑Inspired Multi‑Agent Harness

The article details how a GAN‑inspired multi‑agent harness—combining a generator, an evaluator, and a planner—overcomes context‑window anxiety and self‑evaluation bias, enabling Claude to produce higher‑quality front‑end designs and full‑stack applications through iterative scoring, sprint contracts, and extensive cost‑benefit experiments.

AI EngineeringFull-Stack DevelopmentGAN
0 likes · 19 min read
Boosting Claude’s Front‑End Development with a GAN‑Inspired Multi‑Agent Harness
Sohu Smart Platform Tech Team
Sohu Smart Platform Tech Team
Sep 12, 2025 · Artificial Intelligence

How AI is Revolutionizing Video Creation: From Text‑to‑Video to Real‑Time Editing

This article systematically explores the technical evolution, core principles, and emerging innovations of AI‑generated video, covering generation methods, GAN and diffusion models, transformer‑based DiT architectures, efficiency‑boosting NCR, audio‑visual V2A integration, and real‑world applications across media, education, and commerce.

AI video generationDiffusion ModelsGAN
0 likes · 25 min read
How AI is Revolutionizing Video Creation: From Text‑to‑Video to Real‑Time Editing
IT Services Circle
IT Services Circle
Sep 5, 2025 · Artificial Intelligence

10 Must‑Know Tencent AI Interview Topics: Overfitting, Dropout, Transformers & Beyond

This article compiles the ten core questions from a Tencent algorithm interview, covering overfitting, regularization, generalization error, dropout, residual connections, attention, embeddings, BART vs BERT, instruction‑tuning data, LLM hallucination, and why GANs collapse more than diffusion models, with concise explanations and interview‑ready tips.

GANLLMRegularization
0 likes · 22 min read
10 Must‑Know Tencent AI Interview Topics: Overfitting, Dropout, Transformers & Beyond
Architects Research Society
Architects Research Society
Sep 4, 2025 · Artificial Intelligence

Choosing the Right Generative AI Model: Transformers, Diffusion, GANs & RNNs Explained

This article outlines the four dominant generative AI architectures—Transformers, diffusion models, GANs, and RNNs—explaining their core mechanisms, key capabilities, and typical application domains such as chatbots, image creation, deep‑fake media, and time‑series analysis, helping readers choose the right model for their needs.

AI applicationsGANRNN
0 likes · 3 min read
Choosing the Right Generative AI Model: Transformers, Diffusion, GANs & RNNs Explained
NewBeeNLP
NewBeeNLP
Nov 11, 2024 · Artificial Intelligence

Inside MIT’s Deep Generative Models Course: Topics, Schedule, and Resources

MIT’s 6.S978 Deep Generative Models seminar, taught by Associate Professor He Kaiming, offers graduate students a 15‑week deep dive into VAEs, autoregressive models, GANs, diffusion techniques, and cross‑disciplinary applications, with detailed weekly topics, required assignments, and publicly available lecture PDFs.

Deep Generative ModelsDiffusion ModelsGAN
0 likes · 5 min read
Inside MIT’s Deep Generative Models Course: Topics, Schedule, and Resources
DataFunSummit
DataFunSummit
May 6, 2024 · Artificial Intelligence

Advances, Model Types, and Open Challenges of AI‑Generated Content (AIGC) with XiaoBu’s Image Generation Progress

This article reviews the definition, key metrics, and major model families of AI‑generated content, details XiaoBu’s recent breakthroughs in image generation, and discusses open research problems such as evaluation gaps, transformer limitations, and the need for richer multimodal intelligence representations.

AIGCGANGenerative Models
0 likes · 14 min read
Advances, Model Types, and Open Challenges of AI‑Generated Content (AIGC) with XiaoBu’s Image Generation Progress
AI Algorithm Path
AI Algorithm Path
Apr 5, 2024 · Artificial Intelligence

Master CNN, RNN, GAN, and Transformer Architectures in One Guide

This article provides a friendly, step‑by‑step overview of five core deep‑learning architectures—CNN, RNN, GAN, Transformers, and encoder‑decoder—explaining their structures, key components, and typical use cases in image and natural‑language processing.

CNNDeep LearningEncoder-Decoder
0 likes · 12 min read
Master CNN, RNN, GAN, and Transformer Architectures in One Guide
DaTaobao Tech
DaTaobao Tech
Feb 28, 2024 · Artificial Intelligence

A Survey of Image Quality Evaluation Metrics for Text-to-Image Generation

The survey traces the evolution of image‑quality evaluation for text‑to‑image generation—from early handcrafted edge and color cues, through GAN‑era similarity scores such as IS, FID and KID, to modern perceptual and CLIP‑based metrics like LPIPS, CLIPScore, TRIQ, IQT and human‑preference models—highlighting a shift toward semantic, aesthetic, and text‑image alignment measures and forecasting domain‑specific metrics for future diffusion models.

Evaluation MetricsGANGenerative Models
0 likes · 18 min read
A Survey of Image Quality Evaluation Metrics for Text-to-Image Generation
Kuaishou Tech
Kuaishou Tech
Dec 28, 2023 · Artificial Intelligence

Kuaishou Audio Team Wins ICASSP 2024 SSI and PLC Challenges with Advanced Speech Enhancement and Packet Loss Concealment

The Kuaishou audio team secured first place in both the ICASSP 2024 Speech Signal Improvement and Audio Deep Packet Loss Concealment challenges by deploying a two‑stage GAN‑based speech enhancement system and a hybrid time‑frequency packet‑loss concealment model that dramatically improve real‑time communication quality.

Audio ProcessingGANICASSP 2024
0 likes · 8 min read
Kuaishou Audio Team Wins ICASSP 2024 SSI and PLC Challenges with Advanced Speech Enhancement and Packet Loss Concealment
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Nov 9, 2023 · Artificial Intelligence

How Wav2Lip Achieves Accurate Speech‑Driven Lip Sync with Expert Discriminators

The article analyzes the limitations of traditional speech‑driven lip‑sync methods and explains how Wav2Lip introduces a pretrained multi‑frame expert sync discriminator, a two‑stage GAN training pipeline, and a specialized generator architecture to produce high‑quality, audio‑aligned facial videos.

Computer VisionDeep LearningGAN
0 likes · 7 min read
How Wav2Lip Achieves Accurate Speech‑Driven Lip Sync with Expert Discriminators
php Courses
php Courses
Aug 26, 2023 · Artificial Intelligence

Understanding Generative AI: Concepts, Common Models, and Development Guide

Generative AI, a branch of artificial intelligence that creates novel content such as text, images, and music, works by learning patterns from training data, with common models including GANs, VAEs, autoregressive and Transformer-based architectures, and its development involves task definition, data preparation, model design, training, evaluation, and ethical considerations.

Artificial IntelligenceGANModel Development
0 likes · 8 min read
Understanding Generative AI: Concepts, Common Models, and Development Guide
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jul 31, 2023 · Artificial Intelligence

Overview of Deep Neural Network Architectures

This article provides a comprehensive overview of deep neural network families, introducing twelve major architectures—including Feedforward, CNN, RNN, LSTM, DBN, GAN, Autoencoder, Residual, Capsule, Transformer, Attention, and Deep Reinforcement Learning—explaining their principles, structures, training methods, and offering Python/TensorFlow/PyTorch code examples.

CNNDeep LearningGAN
0 likes · 29 min read
Overview of Deep Neural Network Architectures
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Jul 24, 2023 · Artificial Intelligence

NetShare: An End-to-End System for GAN-Based IP Header Trace Packet Generation

This article presents NetShare, an end-to-end framework that uses time‑series GANs combined with domain‑specific encoding to synthesize privacy‑preserving IP header and flow traces, achieving up to 46% higher accuracy than prior generative baselines while improving the fidelity‑privacy trade‑off.

GANIP Header TracingNetShare
0 likes · 7 min read
NetShare: An End-to-End System for GAN-Based IP Header Trace Packet Generation
Meituan Technology Team
Meituan Technology Team
Jun 15, 2023 · Artificial Intelligence

Meituan Technical Team's 8 CVPR 2023 Papers: Overview and Insights

This article reviews eight CVPR 2023 papers selected by Meituan’s technology team, covering self‑supervised learning, domain adaptation, federated learning, object detection, 3D reconstruction, GAN‑based pre‑training, RGB‑T tracking, vision‑language navigation, and visual‑textual layout generation, highlighting each work’s methodology, experiments, and reported performance gains.

3D Object DetectionCVPR 2023Computer Vision
0 likes · 15 min read
Meituan Technical Team's 8 CVPR 2023 Papers: Overview and Insights
Alimama Tech
Alimama Tech
May 31, 2023 · Artificial Intelligence

Unsupervised Domain Adaptation with Pixel-level Discriminator for Image-aware Layout Generation

Alibaba Mama’s team introduces PDA‑GAN, an unsupervised domain‑adaptation framework employing a lightweight pixel‑level discriminator to align repaired and original image features, enabling image‑aware layout generation that outperforms prior methods on visual‑quality and layout metrics for advertising creatives.

GANlayout generationpixel-level discriminator
0 likes · 10 min read
Unsupervised Domain Adaptation with Pixel-level Discriminator for Image-aware Layout Generation
DataFunTalk
DataFunTalk
May 10, 2023 · Artificial Intelligence

AI‑Driven Predictive Maintenance for NIO Power: GAN and Conceptor Techniques for PHM

This article presents NIO Power's intelligent equipment health management solution, detailing business background, operational challenges, PHM difficulties, and frontier AI technologies such as GAN‑based unsupervised anomaly detection and Conceptor‑based small‑sample fault diagnosis, illustrated with real‑world case studies and a comprehensive Q&A.

ConceptorGANNIO Power
0 likes · 28 min read
AI‑Driven Predictive Maintenance for NIO Power: GAN and Conceptor Techniques for PHM
AntTech
AntTech
Dec 20, 2022 · Artificial Intelligence

Towards Smooth Video Composition: A New Benchmark for GAN‑Based Video Generation

Researchers from multiple institutions propose a GAN‑based video generation framework that explicitly models short‑, medium‑, and long‑range temporal relations, introduces B‑spline motion embeddings and temporal shift modules, and demonstrates substantial quality improvements across several video datasets.

B-splineGANStyleGAN-V
0 likes · 7 min read
Towards Smooth Video Composition: A New Benchmark for GAN‑Based Video Generation
HelloTech
HelloTech
Oct 19, 2022 · Artificial Intelligence

Intelligent Creative System: Types, Quality Evaluation, Generation Models, and Optimization

The Intelligent Creative System defines advertising creatives across formats, evaluates image and text quality using reference‑based metrics and models like DeepBIQ, generates multimodal ads via GANs and Transformers, and selects optimal variants through bandit‑based CTR prediction and multimodal fusion, enabling scalable, data‑driven creative production.

AIBandit ModelGAN
0 likes · 10 min read
Intelligent Creative System: Types, Quality Evaluation, Generation Models, and Optimization
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Oct 11, 2022 · Artificial Intelligence

GANomaly: Theory and Source Code Analysis

This article explains the GANomaly model for semi‑supervised anomaly detection, detailing its generator‑encoder‑discriminator architecture, loss functions, testing phase scoring, and provides annotated PyTorch source code to help readers implement and understand the approach.

Deep LearningEncoder-DecoderGAN
0 likes · 15 min read
GANomaly: Theory and Source Code Analysis
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Oct 8, 2022 · Artificial Intelligence

Wasserstein GAN (WGAN): Theory and Hands‑On Implementation

This article explains why traditional GANs suffer from training instability, introduces the Wasserstein (Earth‑Mover) distance as a smoother alternative, derives the WGAN objective, discusses Lipschitz constraints, and provides practical PyTorch code modifications to convert a vanilla GAN into a stable WGAN.

Deep LearningGANPyTorch
0 likes · 21 min read
Wasserstein GAN (WGAN): Theory and Hands‑On Implementation
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Sep 28, 2022 · Artificial Intelligence

EGBAD: Efficient GAN‑Based Anomaly Detection – Theory and Practical Implementation

This article introduces the EGBAD model, an efficient GAN‑based anomaly detection method that replaces AnoGAN's costly latent variable search with an encoder, provides detailed PyTorch code for data loading, model construction, training, and inference, and compares its testing speed with AnoGAN.

DiscriminatorEGBADEncoder
0 likes · 18 min read
EGBAD: Efficient GAN‑Based Anomaly Detection – Theory and Practical Implementation
DataFunSummit
DataFunSummit
Sep 4, 2022 · Artificial Intelligence

Sparse Features in Machine Learning: Challenges, NVIDIA Ampere Structured Sparsity, Knowledge Distillation, and GAN Model Compression

This talk explores the challenges and opportunities of leveraging sparsity in machine learning models, covering fine‑grained and coarse‑grained sparsity, NVIDIA Ampere’s 2:4 structured sparsity, knowledge‑distillation techniques for converting unstructured to structured sparsity, and model compression strategies for generative adversarial networks.

Deep LearningGANGPU Acceleration
0 likes · 14 min read
Sparse Features in Machine Learning: Challenges, NVIDIA Ampere Structured Sparsity, Knowledge Distillation, and GAN Model Compression
Beike Product & Technology
Beike Product & Technology
Aug 12, 2022 · Artificial Intelligence

Green Area Generation Method Based on Pix2pix Model

This paper proposes a pix2pix‑based method to automatically generate green areas for large‑scale outdoor 3D scene modeling, detailing dataset creation via OpenCV segmentation, model training, region partitioning, and experimental results showing a 93.8% acceptance rate, significantly improving efficiency over manual drawing.

3D modelingComputer VisionGAN
0 likes · 14 min read
Green Area Generation Method Based on Pix2pix Model
Alimama Tech
Alimama Tech
Jul 27, 2022 · Artificial Intelligence

Content-aware Automatic Graphic Layout Generation

The paper introduces a perception‑driven automatic graphic layout system that aligns advertising creatives with product images via a domain‑alignment module and generates content‑aware layouts using a multi‑scale CNN‑Transformer generator, achieving superior aesthetic quality and lower element overlap compared with existing template‑based and deep‑learning methods.

GANImage Generationcontent-aware
0 likes · 10 min read
Content-aware Automatic Graphic Layout Generation
Code DAO
Code DAO
Jun 3, 2022 · Artificial Intelligence

Decomposing PointGAN: Teaching a Machine to Generate a Single Point

This article walks through building and analyzing a minimal GAN—PointGAN—that learns to output the single value 1, covering the linear generator, a two‑layer discriminator, training loops, loss visualizations, instability diagnostics, and practical fixes such as loss easing, weighted examples, weight decay, and noisy generator parameters.

DiscriminatorGANNoise Injection
0 likes · 24 min read
Decomposing PointGAN: Teaching a Machine to Generate a Single Point
DataFunTalk
DataFunTalk
May 28, 2022 · Artificial Intelligence

Adversarial Examples for Captcha: Techniques, Applications, and Future Directions

This article presents a comprehensive overview of adversarial example research applied to captcha systems, covering the definition and history of adversarial attacks, geometric‑aware generation frameworks, FGSM‑based attack variants, experimental results, trade‑offs between image quality and attack strength, and future work such as AdvGAN integration.

AI SafetyDeep LearningFGSM
0 likes · 14 min read
Adversarial Examples for Captcha: Techniques, Applications, and Future Directions
Alimama Tech
Alimama Tech
Apr 13, 2022 · Artificial Intelligence

Brand Advertising Value Modeling: From Instant CTR to Deep CVR and Incremental Uplift

Alibaba Mama’s brand advertising value system evolves from instant CTR to deep CVR and causal uplift modeling, employing focal loss, multi‑task training, GAN‑based uplift, enriched user‑sequence and UID embeddings, which together improve conversion lift, QINI, and interaction metrics while mitigating exposure bias and delayed feedback.

CTRCVRGAN
0 likes · 16 min read
Brand Advertising Value Modeling: From Instant CTR to Deep CVR and Incremental Uplift
Kuaishou Tech
Kuaishou Tech
Feb 25, 2022 · Artificial Intelligence

Reference‑Guided Image Synthesis Assessment (RISA): Unsupervised Training for Single‑Image Quality Evaluation

The paper presents RISA, a reference‑guided image synthesis assessment model that learns to score the quality of a single generated image without human‑labeled data by leveraging GAN intermediate outputs, pixel‑wise interpolation, multiple binary classifiers, and contrastive learning, achieving results comparable to human perception and earning an AAAI 2022 oral presentation.

AIGANRISA
0 likes · 8 min read
Reference‑Guided Image Synthesis Assessment (RISA): Unsupervised Training for Single‑Image Quality Evaluation
IT Services Circle
IT Services Circle
Feb 22, 2022 · Artificial Intelligence

Magical Anime Portraits and SofGAN: AI-Powered Anime Avatar Generation

This article introduces two AI-driven anime portrait tools—Magical Anime Portraits and the open‑source SofGAN project—explaining their workflow, underlying GAN technology, related research, and how they enable users to create unique, customizable anime avatars without manual drawing.

AIAnime AvatarGAN
0 likes · 6 min read
Magical Anime Portraits and SofGAN: AI-Powered Anime Avatar Generation
Code DAO
Code DAO
Dec 11, 2021 · Artificial Intelligence

Using DCGAN to Generate Synthetic Marine Plastic Images

This article explains how to apply a Deep Convolutional GAN in PyTorch to create realistic synthetic images of marine plastic, addressing dataset scarcity, detailing the network architecture, training procedure, and showing loss curves and generated samples.

DCGANGANImage Generation
0 likes · 13 min read
Using DCGAN to Generate Synthetic Marine Plastic Images
iQIYI Technical Product Team
iQIYI Technical Product Team
Dec 10, 2021 · Artificial Intelligence

GAN-based Cold-Start Solution for New Video Recommendation in Short Video Systems

iQIYI’s short‑video team solves the new‑video cold‑start problem by using a GAN that generates latent user features from video attributes and a discriminator to validate them, then matches these vectors to real users via cosine similarity, achieving double‑digit gains in exposure, CTR, and watch time.

GANcold startrecommendation system
0 likes · 13 min read
GAN-based Cold-Start Solution for New Video Recommendation in Short Video Systems
DataFunTalk
DataFunTalk
Aug 10, 2021 · Artificial Intelligence

Practical Deep Learning Tricks: Cyclic LR, Flooding, Warmup, RAdam, Adversarial Training, Focal Loss, Dropout, Normalization, ReLU, Group Normalization, Label Smoothing, Wasserstein GAN, Skip Connections, Weight Initialization

This article presents a concise collection of practical deep‑learning techniques—including cyclic learning‑rate, flooding, warmup, RAdam, adversarial training, focal loss, dropout, various normalization methods, ReLU, group normalization, label smoothing, Wasserstein GAN, skip connections, and weight initialization—along with code snippets and references for implementation.

Deep LearningGANRegularization
0 likes · 8 min read
Practical Deep Learning Tricks: Cyclic LR, Flooding, Warmup, RAdam, Adversarial Training, Focal Loss, Dropout, Normalization, ReLU, Group Normalization, Label Smoothing, Wasserstein GAN, Skip Connections, Weight Initialization
Alimama Tech
Alimama Tech
Jun 24, 2021 · Artificial Intelligence

One‑Stage Training for Generative Adversarial Networks (OSGAN): Methodology and Efficiency Analysis

The OSGAN method introduced by Alibaba’s Mama team and Prof. Song Ming‑Li merges generator and discriminator updates into a single stage, cutting GAN training time by roughly 1.5‑1.7× while maintaining performance, and is validated on symmetric and asymmetric DCGANs with open‑source code.

Computer VisionDeep LearningGAN
0 likes · 10 min read
One‑Stage Training for Generative Adversarial Networks (OSGAN): Methodology and Efficiency Analysis
DataFunTalk
DataFunTalk
May 22, 2021 · Artificial Intelligence

Baidu's Video Foundation Technology Architecture and Key AI Techniques

This article presents an overview of Baidu's video foundation technology architecture, covering the video R&D platform, core AI techniques for video understanding, editing, surveillance, and general vision, and detailing innovations such as Attention‑Cluster networks, cross‑modality attention with graph convolution, GANs, super‑resolution, and adaptive encoding.

Adaptive EncodingAttention MechanismGAN
0 likes · 14 min read
Baidu's Video Foundation Technology Architecture and Key AI Techniques
Kuaishou Large Model
Kuaishou Large Model
Apr 1, 2021 · Artificial Intelligence

How Kuaishou Y‑Tech Leverages GANs for Real‑Time Face Attribute Editing in Short Videos

This article details Kuaishou Y‑Tech's practical deployment of GAN‑based high‑precision face attribute editing—covering gender, age, hair, and expression transformations—for short‑video effects, discussing background, business applications, technical challenges, and solutions across data preparation, model training, and mobile deployment.

Computer VisionGANKuaishou
0 likes · 15 min read
How Kuaishou Y‑Tech Leverages GANs for Real‑Time Face Attribute Editing in Short Videos
DataFunSummit
DataFunSummit
Dec 3, 2020 · Artificial Intelligence

GAN Fundamentals, Variants, and Practical Applications in Image Style Transfer and Handwriting Font Generation

This article provides a comprehensive overview of Generative Adversarial Networks, covering their original formulation, training dynamics, loss functions, major variants such as DCGAN and WGAN, and practical implementations for image‑to‑image translation, style transfer, and handwriting font synthesis at Laiye Technology.

Computer VisionDeep LearningGAN
0 likes · 28 min read
GAN Fundamentals, Variants, and Practical Applications in Image Style Transfer and Handwriting Font Generation
Laiye Technology Team
Laiye Technology Team
Nov 25, 2020 · Artificial Intelligence

Comprehensive Overview of GANs: History, Improvements, Applications, and Handwriting Style Transfer

This article provides an in‑depth overview of Generative Adversarial Networks (GANs), covering their original formulation, major variants such as DCGAN and WGAN, challenges like mode collapse, image‑to‑image translation techniques (cGAN, pix2pix, CycleGAN), and practical handwriting style‑transfer implementations using BicycleGAN and Zi2Zi.

GANGenerative Adversarial NetworksImage-to-Image Translation
0 likes · 27 min read
Comprehensive Overview of GANs: History, Improvements, Applications, and Handwriting Style Transfer
Tencent Music Tech Team
Tencent Music Tech Team
Oct 26, 2020 · Artificial Intelligence

Phase‑Aware Music Super‑Resolution Using Generative Adversarial Networks (INTERSPEECH 2020)

At INTERSPEECH 2020 the authors introduced a phase‑aware music super‑resolution system that uses a frequency‑domain GAN combined with an enhanced Griffin‑Lim algorithm to reconstruct missing high‑frequency magnitude and phase, delivering brighter, louder, and more natural‑sounding recordings that surpass traditional interpolation and naive phase‑flipping methods.

GANINTERSPEECH 2020audio super-resolution
0 likes · 7 min read
Phase‑Aware Music Super‑Resolution Using Generative Adversarial Networks (INTERSPEECH 2020)
Programmer DD
Programmer DD
Aug 12, 2020 · Artificial Intelligence

Turn Photos and Videos into Cartoons with the Open‑Source Cartoonize AI

Cartoonize is an open‑source web application that leverages a white‑box GAN model to convert images and short videos into high‑quality cartoon style, offering easy Docker or virtualenv installation, detailed usage instructions, and insights into the underlying research paper.

AIDockerGAN
0 likes · 9 min read
Turn Photos and Videos into Cartoons with the Open‑Source Cartoonize AI
DataFunTalk
DataFunTalk
Jun 22, 2020 · Artificial Intelligence

Ctrip's Automated Iterative Anti‑Fraud Modeling Framework for Payment Risk

The article describes Ctrip's payment fraud risk characteristics, a comprehensive automated iterative anti‑fraud model framework—including variable system, GAN‑augmented sample generation, RNN behavior encoding, and tree‑based classifiers—and demonstrates how this approach restores recall performance compared with traditional static models.

GANRNNRisk Modeling
0 likes · 12 min read
Ctrip's Automated Iterative Anti‑Fraud Modeling Framework for Payment Risk
Programmer DD
Programmer DD
Apr 24, 2020 · Artificial Intelligence

Turn Photos into Studio Ghibli‑Style Anime with AnimeGAN – A Hands‑On Guide

This article introduces AnimeGAN, a lightweight GAN that converts real photos into Japanese anime‑style illustrations, explains its architecture, loss functions, model size advantages, and provides step‑by‑step instructions with code for setting up, training, and testing the TensorFlow implementation.

AnimeGANDeep LearningGAN
0 likes · 8 min read
Turn Photos into Studio Ghibli‑Style Anime with AnimeGAN – A Hands‑On Guide
DataFunTalk
DataFunTalk
Jan 16, 2020 · Artificial Intelligence

Voice Conversion: Fundamentals, Methods, and iQIYI Applications

This article provides a comprehensive overview of voice conversion technology, covering its definition, parallel and non‑parallel data approaches, classic and deep‑learning methods such as DTW, GMM, seq2seq, PPG, VAE, Flow, GAN, and practical applications and challenges in iQIYI’s products.

ASRDeep LearningGAN
0 likes · 8 min read
Voice Conversion: Fundamentals, Methods, and iQIYI Applications
iQIYI Technical Product Team
iQIYI Technical Product Team
Jan 9, 2020 · Artificial Intelligence

Voice Conversion (VC): Fundamentals, Progress, and Applications

Voice conversion (VC) technology changes a speaker’s timbre and style while keeping the spoken text unchanged, supporting one‑to‑one, many‑to‑one, and many‑to‑many scenarios for medical assistance and entertainment, using parallel or non‑parallel data through methods such as DTW‑aligned frame mapping, attention‑based neural networks, PPG‑LSTM pipelines, VAEs, normalizing‑flow models, and GANs, with iQIYI focusing on non‑parallel data, prosody preservation, and noise‑robust augmentation.

Artificial IntelligenceAudio ProcessingDeep Learning
0 likes · 12 min read
Voice Conversion (VC): Fundamentals, Progress, and Applications
Taobao Frontend Technology
Taobao Frontend Technology
Dec 5, 2019 · Frontend Development

From UI Sketch to Code: Frontend Intelligence Generates 79% of Double‑11 Modules

This article explains how Alibaba's Front‑End Intelligent project automatically converts UI design images into production‑ready code, covering layout analysis, background and foreground processing, a fusion of traditional image algorithms with deep‑learning detection, GAN‑based complex‑background extraction, experimental results and real‑world deployment.

GANImage ProcessingLayout Analysis
0 likes · 21 min read
From UI Sketch to Code: Frontend Intelligence Generates 79% of Double‑11 Modules
Xianyu Technology
Xianyu Technology
Jul 9, 2019 · Artificial Intelligence

Complex Background Content Extraction Using Detection and GAN Networks

The proposed UI2CODE pipeline first recalls UI elements with an object detector, then uses gradient cues to separate simple from complex regions and applies an SRGAN to restore foreground details in challenging backgrounds, achieving higher precision, recall, and localization than GrabCut and Deeplab, though it demands extensive multi‑scale training data.

AIGANImage Processing
0 likes · 4 min read
Complex Background Content Extraction Using Detection and GAN Networks
Beike Product & Technology
Beike Product & Technology
May 23, 2019 · Artificial Intelligence

Practical Applications and Challenges of Machine Learning and AI at QCon Beijing 2019

At QCon Beijing 2019, four Beike technology experts presented the practical use and challenges of machine learning for user profiling, deep‑learning‑based house‑quality scoring, intelligent customer‑service systems, and AI‑driven floor‑plan generation, summarizing the architecture, data pipelines, model evolution, and future improvement directions.

AIDeep LearningGAN
0 likes · 16 min read
Practical Applications and Challenges of Machine Learning and AI at QCon Beijing 2019
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 10, 2019 · Artificial Intelligence

Bilinear Residual Layers: Boosting Text‑Guided Image Editing

This article explores multimodal representation learning by introducing a Bilinear Residual Layer that automatically fuses image and text features, demonstrates its superiority over traditional concatenation and FiLM methods on text‑guided image editing and fashion synthesis tasks, and reports state‑of‑the‑art results on several benchmark datasets.

GANMultimodal Learningbilinear residual layer
0 likes · 17 min read
Bilinear Residual Layers: Boosting Text‑Guided Image Editing
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 imagesComputer VisionFace Detection
0 likes · 8 min read
How to Spot AI‑Generated Fake Faces: Tips, Tricks, and the Tech Behind StyleGAN
360 Quality & Efficiency
360 Quality & Efficiency
Dec 28, 2018 · Artificial Intelligence

SRGAN-Based Image Super-Resolution and MNIST Training Tutorial

This tutorial outlines a curriculum covering open‑source examples for enhancing image resolution using SRGAN, explains GAN‑based super‑resolution concepts, details network architectures and perceptual loss, and provides a simple MNIST training walkthrough with code links and resources.

GANMNISTSRGAN
0 likes · 7 min read
SRGAN-Based Image Super-Resolution and MNIST Training Tutorial
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 19, 2018 · Artificial Intelligence

How Cross‑Domain Embedding Boosts New User Recommendations in Alibaba’s Ecosystem

This article explains the design of a Cross‑Domain Embedding (CSDE) method that transfers Alipay user features to Taobao representations, details its learning and adaptive prediction stages, and shows experimental and online results demonstrating significant conversion‑rate improvements for new and inactive users.

Deep LearningGANconversion rate prediction
0 likes · 15 min read
How Cross‑Domain Embedding Boosts New User Recommendations in Alibaba’s Ecosystem
360 Quality & Efficiency
360 Quality & Efficiency
Oct 26, 2018 · Artificial Intelligence

Machine Learning Methods: Discriminative and Generative Models, Semi‑Supervised Learning, and GAN‑Based Classification

This article explains the distinction between discriminative and generative models, outlines the challenges of limited labeled data, introduces semi‑supervised learning principles, and describes GAN‑based semi‑supervised classification algorithms with illustrative diagrams.

Artificial IntelligenceGANGenerative Models
0 likes · 3 min read
Machine Learning Methods: Discriminative and Generative Models, Semi‑Supervised Learning, and GAN‑Based Classification
21CTO
21CTO
Jul 22, 2018 · Artificial Intelligence

Can AI Seamlessly Cloak Nudity? Unsupervised Image-to-Image Translation with GANs

Researchers propose an unsupervised GAN-based image-to-image translation method that automatically dresses nude women in bikinis, preserving semantic content while removing sensitive parts, using unpaired datasets and Mask‑RCNN background removal, demonstrating impressive visual results without manual annotation.

GANImage-to-Image TranslationUnsupervised Learning
0 likes · 10 min read
Can AI Seamlessly Cloak Nudity? Unsupervised Image-to-Image Translation with GANs
Hulu Beijing
Hulu Beijing
Feb 1, 2018 · Artificial Intelligence

Understanding GANs: Theory, Minimax Game, and Training Challenges

This article introduces Generative Adversarial Networks (GANs), explains their minimax formulation, value function, Jensen‑Shannon divergence, common variants, and practical training issues such as gradient saturation, while also previewing the next topic on Hidden Markov Models.

Deep LearningGANGenerative Adversarial Networks
0 likes · 11 min read
Understanding GANs: Theory, Minimax Game, and Training Challenges
21CTO
21CTO
Oct 9, 2017 · Artificial Intelligence

How Wukong’s AI Porn Detection System Achieves 99.5% Accuracy

This article explains the challenges of image‑based porn detection, details the multi‑label classification approach of the Wukong system, and reveals the deep‑learning techniques—including CNN evolution, transfer learning, loss functions, adversarial training, and GAN‑based data augmentation—that enable over 99.5% accuracy with massive daily request volumes.

CNNGANImage Classification
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How Wukong’s AI Porn Detection System Achieves 99.5% Accuracy
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 7, 2017 · Artificial Intelligence

Probabilistic Pair Recommendations & IRGAN: Boosting E‑commerce Click‑Through

This article summarizes two SIGIR 2017 papers: one introduces a probabilistic latent‑class model for shopping‑pair push recommendations that improves e‑commerce click‑through rates by leveraging co‑purchase and view‑then‑purchase graphs, and the other presents IRGAN, a GAN‑based framework that unifies generative and discriminative information‑retrieval models, achieving state‑of‑the‑art results across web search, recommendation, and QA tasks.

GANe‑commerceinformation retrieval
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Probabilistic Pair Recommendations & IRGAN: Boosting E‑commerce Click‑Through
Qunar Tech Salon
Qunar Tech Salon
Apr 24, 2017 · Artificial Intelligence

Advances in Image Super-Resolution Using Deep Learning: CNN, GAN, and PixelCNN

Recent advances in image super-resolution leverage deep learning techniques such as convolutional neural networks, residual learning, perceptual loss, generative adversarial networks, and PixelCNN to reconstruct high-resolution details from low-resolution inputs, addressing challenges of scalability, training efficiency, and multi-scale upscaling.

CNNDeep LearningGAN
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Advances in Image Super-Resolution Using Deep Learning: CNN, GAN, and PixelCNN