會議論文
| 學年 | 108 |
|---|---|
| 學期 | 2 |
| 發表日期 | 2020-03-05 |
| 作品名稱 | Occluded Traffic Signs Recognition |
| 作品名稱（其他語言） | |
| 著者 | Shwu-Huey Yen; Chun-Yung Shu; Hui-Huang Hsu |
| 作品所屬單位 | |
| 出版者 | |
| 會議名稱 | Future of Information and Communication Conference (FICC 2020) |
| 會議地點 | San Francisco, USA |
| 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. |
| 關鍵字 | Occlusion;Traffic sign;Recognition;GTSRB;Convolutional Neural Network;Mask |
| 語言 | en_US |
| 收錄於 | |
| 會議性質 | 國際 |
| 校內研討會地點 | 無 |
| 研討會時間 | 20200305~20200306 |
| 通訊作者 | |
| 國別 | USA |
| 公開徵稿 | |
| 出版型式 | |
| 出處 | Advances in Intelligent Systems and Computing 1130 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120549 ) |