Efficient Object Detection and Intelligent Information Display Using YOLOv4-Tiny
Ying-Tung Hsiao,
Jia-Shing Sheu,
Hsu Ma
Abstract:This study aims to develop an innovative image recognition and information display approach based on you only look once version 4 (YOLOv4)-tiny framework. The lightweight YOLOv4-tiny model is modified by replacing convolutional modules with Fire modules to further reduce its parameters. Performance reductions are offset by including spatial pyramid pooling, and they also improve the model’s detection ability for objects of various sizes. The pattern analysis, statistical modeling, and computational learning vi… Show more
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