Feature Extraction

DataFunSummit

Feb 26, 2025 · Artificial Intelligence

Applying Multimodal Large Models to Music Recommendation at NetEase Cloud Music

This article details how NetEase Cloud Music leverages multimodal large language models to improve music recommendation across daily, personalized, and playlist scenarios by extracting rich audio, text, and visual features, addressing data skew, cold‑start challenges, and achieving measurable gains in user engagement and distribution efficiency.

Feature ExtractionNetEase Cloud MusicRecommendation systems

0 likes · 12 min read

Applying Multimodal Large Models to Music Recommendation at NetEase Cloud Music

php中文网 Courses

Oct 23, 2024 · Artificial Intelligence

Data Dimensionality Reduction and Feature Extraction with PHP

This article explains the concepts of data dimensionality reduction and feature extraction in machine learning and demonstrates how to implement them in PHP using the PHP‑ML library, including installation, data preprocessing, PCA-based reduction, and feature extraction with token vectorization and TF‑IDF.

Feature ExtractionPCAPHP-ML

0 likes · 5 min read

Data Dimensionality Reduction and Feature Extraction with PHP

php中文网 Courses

Jun 13, 2024 · Artificial Intelligence

Using PHP for Data Dimensionality Reduction and Feature Extraction

This article explains the importance of data dimensionality reduction and feature extraction in machine learning, and provides a step‑by‑step guide with PHP code examples—including library installation, data preprocessing, PCA‑based reduction, and feature selection techniques—demonstrating how to handle large datasets efficiently.

Feature ExtractionPCAPHP

0 likes · 6 min read

Using PHP for Data Dimensionality Reduction and Feature Extraction

Test Development Learning Exchange

Mar 28, 2024 · Artificial Intelligence

Introduction to librosa: Audio Loading, Feature Extraction, and Visualization with Python

This article introduces the Python library librosa, outlines its main audio processing features such as loading, visualization, MFCC, pitch detection, chromagram, and rhythm analysis, and provides complete code examples for each operation.

Audio ProcessingFeature ExtractionMIR

0 likes · 7 min read

Introduction to librosa: Audio Loading, Feature Extraction, and Visualization with Python

NetEase LeiHuo Testing Center

Feb 2, 2024 · Game Development

Automated Audio Testing for FPS Games: Process, Tools, and Similarity Measurement

This article presents a comprehensive guide to automating audio testing in first‑person shooter games, covering common audio bugs, a step‑by‑step recording workflow, feature extraction techniques, similarity metrics, and practical toolchains such as Soundcard, fmedia, VBCable, and librosa.

AutomationFeature ExtractionGame development

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Automated Audio Testing for FPS Games: Process, Tools, and Similarity Measurement

TAL Education Technology

Aug 31, 2023 · Artificial Intelligence

Research on Content-Based Image Retrieval Techniques

This article reviews the fundamentals, feature extraction methods, evaluation metrics, and common datasets of content‑based image retrieval (CBIR), discussing traditional low‑level features, local descriptors, unsupervised and supervised learning approaches, and recent deep‑learning models for improving retrieval performance.

CBIRFeature Extractiondatasets

0 likes · 13 min read

Research on Content-Based Image Retrieval Techniques

Rare Earth Juejin Tech Community

Jul 25, 2023 · Artificial Intelligence

Building a Reverse Image Search Engine with Geometric Distance, ResNet Feature Embeddings, Clustering, and Milvus Vector Database

This article walks through implementing a reverse image search system, starting with simple pixel‑based geometric distance, then improving accuracy using ResNet‑derived feature embeddings, accelerating queries with K‑means clustering, and finally deploying a Milvus vector database for fast, scalable similarity retrieval.

ClusteringFeature ExtractionMilvus

0 likes · 17 min read

Building a Reverse Image Search Engine with Geometric Distance, ResNet Feature Embeddings, Clustering, and Milvus Vector Database

High Availability Architecture

Apr 27, 2023 · Artificial Intelligence

Design and Optimization of Bilibili's Large‑Scale Video Duplicate Detection System

This article describes the design, algorithmic improvements, and engineering performance optimizations of Bilibili's massive video duplicate detection (collision) system, covering challenges of low‑edit‑degree reposts, two‑stage retrieval, self‑supervised feature extraction, GPU‑accelerated preprocessing, and the resulting gains in accuracy and throughput.

BilibiliFeature ExtractionVector Search

0 likes · 17 min read

Design and Optimization of Bilibili's Large‑Scale Video Duplicate Detection System

Bilibili Tech

Apr 21, 2023 · Artificial Intelligence

Design and Optimization of Bilibili's Large-Scale Video Duplicate Detection System

Bilibili built a massive video‑duplicate detection platform that trains a self‑supervised ResNet‑50 feature extractor, removes black borders, and uses a two‑stage ANN‑plus‑segment‑level matching pipeline accelerated by custom GPU decoding and inference, boosting duplicate rejection 7.5×, recall 3.75×, and cutting manual misses from 65 to 5 per day.

Feature ExtractionGPU AccelerationSystem Architecture

0 likes · 19 min read

DataFunSummit

Mar 12, 2023 · Artificial Intelligence

PaddleBox and FeaBox: GPU‑Based Large‑Scale Sparse Model Training and Integrated Feature Extraction Frameworks at Baidu

The article introduces PaddleBox and FeaBox, two GPU‑driven frameworks designed for massive sparse DNN training and unified feature extraction, detailing their architecture, performance advantages, hardware‑software co‑design challenges, and successful deployment across Baidu's advertising systems.

AI infrastructureFeaBoxFeature Extraction

0 likes · 24 min read

PaddleBox and FeaBox: GPU‑Based Large‑Scale Sparse Model Training and Integrated Feature Extraction Frameworks at Baidu

Baidu Intelligent Testing

Aug 19, 2021 · Big Data

Overview of Baidu's Wanxiang System for Large‑Scale Rich Media Processing

The article provides a comprehensive overview of Baidu's Wanxiang system, detailing how it tackles the challenges of massive image and video data processing, feature extraction, cross‑media indexing, and real‑time retrieval to support modern search engine products.

BaiduBig DataFeature Extraction

0 likes · 13 min read

Overview of Baidu's Wanxiang System for Large‑Scale Rich Media Processing

Tencent Advertising Technology

Jun 22, 2021 · Artificial Intelligence

Technical Insights and Solution Strategies from the Tencent Advertising Algorithm Competition – Video Ad Track

The article outlines the Tencent Advertising Algorithm Competition’s video ad challenge, details the paper submission guidelines, and shares a participant’s step‑by‑step technical approach—including baseline experiments, model re‑implementation with Paddle, multimodal feature extraction, optimizer choices, and future improvement directions—providing practical AI insights for multimedia video classification.

Feature ExtractionTencent competitiondeep learning

0 likes · 7 min read

Technical Insights and Solution Strategies from the Tencent Advertising Algorithm Competition – Video Ad Track

360 Quality & Efficiency

Nov 27, 2020 · Artificial Intelligence

Image Similarity Detection Methods: Hashing, Histograms, Feature Matching, BOW+K‑Means, and CNN‑Based Approaches

This article reviews common image similarity detection techniques—including hash-based methods (aHash, pHash, dHash), histogram comparison, feature matching with ORB and SIFT/SURF, bag‑of‑words with K‑Means, and CNN‑based VGG16 features—detailing their algorithms, Python implementations, performance characteristics, and practical considerations.

Feature ExtractionHashingcomputer vision

0 likes · 15 min read

Image Similarity Detection Methods: Hashing, Histograms, Feature Matching, BOW+K‑Means, and CNN‑Based Approaches

DeWu Technology

Nov 18, 2020 · Artificial Intelligence

Evolution and Technical Analysis of Dewu Photo Search

Dewu Photo Search evolved from a limited Aliyun‑based prototype to a self‑developed pipeline using EfficientNet detection and 128‑dim embeddings, boosting top‑1 shoe accuracy over 100 % and overall precision by up to 41 %, while reducing latency and improving scalability despite remaining stability challenges.

Feature ExtractionImage Searchcomputer vision

0 likes · 10 min read

Evolution and Technical Analysis of Dewu Photo Search

System Architect Go

Mar 30, 2020 · Artificial Intelligence

Overview of Image Search System

This article explains the fundamentals of building an image‑by‑image search system, covering image feature extraction methods such as hashing, traditional descriptors, CNN‑based vectors, and the use of vector search engines like Milvus for similarity retrieval.

CNNFeature ExtractionImage Search

0 likes · 6 min read

iQIYI Technical Product Team

Mar 27, 2020 · Artificial Intelligence

Beihang Team's Video Copyright Detection Solution: Frame Sampling, Feature Extraction, and Retrieval Matching

The Beihang University team’s video copyright detection solution samples frames every 200 ms, extracts 512‑dimensional ResNet‑18 features, and uses handcrafted cosine‑similarity matching to identify source videos and plagiarized segments, all while operating on limited hardware without training any models.

Feature ExtractionVideo Copyright Detectionalgorithm design

0 likes · 12 min read

Beihang Team's Video Copyright Detection Solution: Frame Sampling, Feature Extraction, and Retrieval Matching

DataFunTalk

Nov 28, 2019 · Artificial Intelligence

Web Data Mining and Page Analysis Techniques for Search Engines

This article explains how search engines collect, analyze, and rank web pages by describing the spider system, HTML and layout tree construction, feature extraction, and machine‑learning based classification methods used to understand page content and improve result relevance.

Feature ExtractionHTML treeSearch Engine

0 likes · 8 min read

Web Data Mining and Page Analysis Techniques for Search Engines

58 Tech

Oct 10, 2019 · Big Data

Optimizing Real‑Time Feature Extraction at 58.com: Migrating from Spark Streaming to Flink

This article describes how 58.com’s commercial engineering team redesigned its real‑time feature‑mining pipeline—replacing a minute‑level Spark Streaming framework with Flink—to achieve sub‑second latency, higher throughput, stronger fault‑tolerance, and end‑to‑end exactly‑once semantics for user‑profile generation in the second‑hand‑car recommendation scenario.

Big DataFeature ExtractionFlink

0 likes · 14 min read

Optimizing Real‑Time Feature Extraction at 58.com: Migrating from Spark Streaming to Flink

DataFunTalk

May 14, 2019 · Artificial Intelligence

A Comprehensive Overview of Image Search Technology: Frameworks, Evolution, and System Architecture

This article provides a thorough introduction to image‑search technology, covering its general framework, offline and online components, feature‑extraction evolution, retrieval engine structures, and architectural challenges such as dynamic indexing, feature synchronization, and high‑throughput low‑latency serving.

Feature ExtractionImage Searchcomputer vision

0 likes · 12 min read

A Comprehensive Overview of Image Search Technology: Frameworks, Evolution, and System Architecture

System Architect Go

Mar 14, 2019 · Artificial Intelligence

Understanding Image Similarity: Image Hashing and Feature-Based Methods

This article explains why simple MD5 checks cannot assess image similarity and introduces two major approaches—image hashing and image feature extraction—detailing their algorithms, practical performance, and how to compare images efficiently using Hamming distance and indexing techniques.

Feature ExtractionHamming distancecomputer vision

0 likes · 7 min read

Understanding Image Similarity: Image Hashing and Feature-Based Methods