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NetEase LeiHuo Testing Center
NetEase LeiHuo Testing Center
Apr 1, 2022 · Artificial Intelligence

Learning OCR for Game Text Recognition: From Data Preparation to CRNN Model Training

This article documents the author’s step‑by‑step journey of building an OCR system for recognizing Chinese characters in a card‑game UI, covering game selection, technical background, data generation, deep‑learning model training with CRNN, real‑image data collection, optimization attempts, and final performance evaluation.

CRNNDeep LearningEasyOCR
0 likes · 15 min read
Learning OCR for Game Text Recognition: From Data Preparation to CRNN Model Training
Cyber Elephant Tech Team
Cyber Elephant Tech Team
Oct 14, 2021 · Artificial Intelligence

Mastering OCR: From Traditional Techniques to Deep Learning Solutions

This article provides a comprehensive overview of Optical Character Recognition, covering its traditional applications, the evolution to deep learning methods, key datasets, popular tools, and practical strategies for tackling diverse OCR challenges in real-world scenarios.

CRNNDeep LearningEAST
0 likes · 18 min read
Mastering OCR: From Traditional Techniques to Deep Learning Solutions
58 Tech
58 Tech
Aug 10, 2021 · Artificial Intelligence

Active Learning and Model Enhancements for Semantic Tag Mining in 58.com Voice Data

This article presents a comprehensive study on extracting semantic tags from 58.com voice data, detailing the use of active learning to address cold‑start problems, comparing keyword matching, XGBoost, TextCNN, CRNN, and an improved Wide&Deep model, and demonstrating significant reductions in labeling effort and superior F1 scores across multiple experiments.

CRNNMachine LearningText Classification
0 likes · 15 min read
Active Learning and Model Enhancements for Semantic Tag Mining in 58.com Voice Data
58 Tech
58 Tech
Nov 16, 2020 · Artificial Intelligence

Iterative Optimization of Voice Endpoint Detection for Voice Robots: From Dual‑Threshold to WebRTC VAD and VADNet

This article details the evolution of the voice endpoint detection (VAD) module in 58.com’s voice robot, comparing a dual‑threshold method, Google’s WebRTC VAD, and the deep‑learning based VADNet, and presents experimental results on accuracy, recall, F1 score and online latency.

CRNNDeep LearningReal-time Communication
0 likes · 14 min read
Iterative Optimization of Voice Endpoint Detection for Voice Robots: From Dual‑Threshold to WebRTC VAD and VADNet