How Baidu’s GNOIMI Powers Billion‑Scale Rich Media Retrieval

Baidu’s rich‑media retrieval system combines CNN‑based feature extraction with an Approximate Nearest Neighbor engine called GNOIMI, employing hierarchical clustering, product quantization, and optimized indexing to achieve sub‑millisecond search over billions of images, videos and audio, supporting anti‑spam, recommendation and risk‑control across dozens of services.

ANNGNOIMIHNSW

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How Baidu’s GNOIMI Powers Billion‑Scale Rich Media Retrieval

Youku Technology

Nov 2, 2018 · Artificial Intelligence

How AI Powers Next‑Gen Multimedia Content Retrieval: From OCR to Knowledge Graphs

This article examines the evolution of search, defines multimedia content retrieval, explores user scenarios such as voice, image, and video input, and details key AI techniques—including OCR, face recognition, and content knowledge graphs—that enable semantic understanding and ranking of video content.

OCRface recognitionknowledge graph

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How AI Powers Next‑Gen Multimedia Content Retrieval: From OCR to Knowledge Graphs

Meitu Technology

Jul 12, 2018 · Artificial Intelligence

DeepHash: Large-Scale Multimedia Content Analysis and Retrieval for Short Video Platforms

DeepHash is Meitu’s large‑scale short‑video analysis and retrieval system that converts deep‑learned visual features into compact binary hash codes via a MobileNet‑based CNN and triplet‑loss training, enabling fast, robust similarity search across billions of videos with sub‑second latency and minimal storage.

feature extractionlarge scalemultimedia retrieval

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DeepHash: Large-Scale Multimedia Content Analysis and Retrieval for Short Video Platforms