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Zhuanzhuan Tech
Zhuanzhuan Tech
Apr 15, 2026 · Artificial Intelligence

Boosting Bag Item Identification with Metric Learning: A ZhiZhuan Case Study

ZhiZhuan’s in‑house “photo‑to‑SKU” system tackles large‑scale bag identification by combining dual‑stage object detection, metric‑learning‑based embedding training, and a hybrid vector‑plus‑scalar retrieval pipeline, achieving superior top‑K accuracy over third‑party solutions while addressing fine‑grained visual nuances and long‑tail SKU coverage.

Deep LearningEmbeddingbag identification
0 likes · 16 min read
Boosting Bag Item Identification with Metric Learning: A ZhiZhuan Case Study
PaperAgent
PaperAgent
Apr 4, 2026 · Artificial Intelligence

Can AI Master Contextual Photo Search? Inside DeepImageSearch, DISBench, and ImageSeeker

This article examines the DeepImageSearch project, which redefines image retrieval as contextual reasoning, introduces the challenging DISBench benchmark for visual agents, and details the ImageSeeker framework that equips models with multi‑tool interaction and hierarchical memory to tackle complex, multi‑event photo queries.

AI agentsBenchmarkDISBench
0 likes · 9 min read
Can AI Master Contextual Photo Search? Inside DeepImageSearch, DISBench, and ImageSeeker
AI Frontier Lectures
AI Frontier Lectures
Mar 13, 2026 · Artificial Intelligence

Can AI Truly Understand Your Photo Album? DeepImageSearch and the DISBench Benchmark

This article introduces DeepImageSearch, a new context‑aware image retrieval paradigm that shifts from isolated semantic matching to multi‑step visual‑history reasoning, presents the challenging DISBench benchmark for evaluating such capabilities, and analyzes why even the strongest multimodal models still fall short.

DISBenchDeepImageSearchMultimodal AI
0 likes · 14 min read
Can AI Truly Understand Your Photo Album? DeepImageSearch and the DISBench Benchmark
TAL Education Technology
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.

CBIRDatasetsDeep Learning
0 likes · 13 min read
Research on Content-Based Image Retrieval Techniques
NetEase LeiHuo Testing Center
NetEase LeiHuo Testing Center
Jun 2, 2023 · Artificial Intelligence

AI Techniques for a Global Search Platform: Word Segmentation, Text Similarity, Image Retrieval, and Multimodal Models

This article shares the development of a global search platform that leverages AI technologies such as Chinese word segmentation, part‑of‑speech tagging, text similarity via Simhash and Synonyms, image similarity using histogram, Hamming distance and ResNet‑50, and multimodal CLIP‑based models to improve search efficiency and accuracy.

AINLPimage retrieval
0 likes · 12 min read
AI Techniques for a Global Search Platform: Word Segmentation, Text Similarity, Image Retrieval, and Multimodal Models
360 Quality & Efficiency
360 Quality & Efficiency
Jul 1, 2022 · Artificial Intelligence

Building an End-to-End Image Search System with Milvus and VGG

This article presents a complete image‑search solution that extracts visual features with the VGG16 model, stores them in the Milvus vector database, and provides a set of web APIs for training, querying, counting, searching, and deleting image vectors, all deployed via Docker containers.

AIDeep LearningMilvus
0 likes · 7 min read
Building an End-to-End Image Search System with Milvus and VGG
58 Tech
58 Tech
Jun 9, 2022 · Artificial Intelligence

Multi‑Label Image Recognition for 58.com: Algorithm Design, Data Construction, and Model Optimization

This article presents a comprehensive study of multi‑label image recognition applied to 58.com’s business scenarios, covering problem motivation, dataset construction, evaluation metrics, mainstream deep‑learning methods, an asymmetric‑loss‑based optimization pipeline, and practical output schemes for recommendation and retrieval.

Computer Visionasymmetric lossdata annotation
0 likes · 17 min read
Multi‑Label Image Recognition for 58.com: Algorithm Design, Data Construction, and Model Optimization
Amap Tech
Amap Tech
Nov 4, 2021 · Artificial Intelligence

POI Signboard Image Retrieval: Technical Solution, Model Design, and Future Directions

To efficiently filter unchanged POI signboards, the authors propose a multimodal image‑retrieval system that combines enhanced global and local visual features with BERT‑encoded OCR text, using metric learning and alignment techniques to achieve over 95 % accuracy while handling occlusion, viewpoint variation, and subtle text changes.

Computer VisionDeep LearningMultimodal Learning
0 likes · 17 min read
POI Signboard Image Retrieval: Technical Solution, Model Design, and Future Directions
Alibaba Cloud Developer
Alibaba Cloud Developer
Nov 4, 2021 · Artificial Intelligence

How AI Powers POI Signboard Image Retrieval for Map Services

This article explains the challenges of POI signboard image retrieval, describes a multimodal deep‑learning solution that combines visual and OCR‑based text features, details data generation, model architecture, loss functions, and presents impressive accuracy improvements and future research directions.

Deep LearningMultimodal LearningPOI mapping
0 likes · 17 min read
How AI Powers POI Signboard Image Retrieval for Map Services
AntTech
AntTech
Apr 15, 2020 · Artificial Intelligence

Ant Financial Research Highlights at WWW2020: Enhanced‑RCNN, IntentDial, Captcha Solver, Billion‑Scale Knapsack, and EET Loss

The article summarizes five Ant Financial papers accepted at WWW2020, covering an efficient sentence‑similarity model (Enhanced‑RCNN), a graph‑based multi‑turn dialogue system (IntentDial), a low‑label captcha recognizer, a solver for billion‑scale knapsack problems, and a novel equal‑distance/equal‑distribution triplet loss for image retrieval.

Ant FinancialDialogue SystemsWWW2020
0 likes · 9 min read
Ant Financial Research Highlights at WWW2020: Enhanced‑RCNN, IntentDial, Captcha Solver, Billion‑Scale Knapsack, and EET Loss