淡江大學機構典藏:Item 987654321/120549
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    題名: Occluded Traffic Signs Recognition
    作者: Yen, Shwu-Huey;Shu, Chun-Yung;Hsu, Hui-Huang
    關鍵詞: Occlusion;Traffic sign;Recognition;GTSRB;Convolutional Neural Network;Mask
    日期: 2020-03-05
    上傳時間: 2021-04-20 12:10:43 (UTC+8)
    摘要: Traffic sign recognition is very important in the intelligent driving. It can remind drivers to react properly to the road condition and increase the driving safety. One of the challenges in recognizing traffic sign is occlusion. In this paper, we focus on this problem particularly in Taipei and the vicinity including Taipei and New Taipei City. We propose a convolution neural network equipped with the regional masks to solve the occlusion traffic sign recognition. Traffic sign images of Taipei and New Taipei City are collected mainly from Google Maps for training and testing. Finally, the proposed method is tested both on our own dataset and German public dataset GTSRB. The experimental results demonstrated the occlusion problem is being greatly alleviated and the result is very promising.
    關聯: Advances in Intelligent Systems and Computing 1130
    DOI: 10.1007/978-3-030-39442-4_58
    顯示於類別:[資訊工程學系暨研究所] 會議論文

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