Real-Time Text Detection and Recognition
원문 초록
Inrecentyears,ConvolutionalNeuralNet-work(CNN) is quite a popular topic, as it is a powerful andintelligent technique that can be applied in various fields.The YOLO is a technique that uses the algorithms for real-time text detection tasks. However, issues like, photometricdistortion and geometric distortion, could affect the systemYOLO accuracy and cause system failure. Therefore, thereare improvements that can make the system work better. Inthis paper, we are going to present our solution - a potentialsolution of a fast and accurate real-time text direction andrecognition system. The paper covers the topic of Real-TimeText detection and recognition in three major areas: 1. videoand image preprocess, 2. Text detection, 3. Text recognition. Asa mature technique, there are many existing methods that canpotentially improve the solution. We will go through some ofthose existing methods in the literature review session. In thisway, we are presenting an industrial strength, high-accuracy,Real-Time Text Detection and recognition tool.
함께 살펴볼 논문
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Stress-testing Machine Generated Text Detection: Shifting Language Models Writing Style to Fool Detectors
The Devil is in Fine-tuning and Long-tailed Problems:A New Benchmark for Scene Text Detection
FAID: Fine-grained AI-generated Text Detection using Multi-task Auxiliary and Multi-level Contrastive Learning
Visual Text Processing: A Comprehensive Review and Unified Evaluation
SemiETS: Integrating Spatial and Content Consistencies for Semi-Supervised End-to-end Text Spotting
Short-PHD: Detecting Short LLM-generated Text with Topological Data Analysis After Off-topic Content Insertion
토론
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