未來展望

經過所有實驗與討論，整理出以下數點作未來改進方向：

1. 將 SVM 車牌偵測的部分換成 YOLOv2，以減少系統架構的複雜度。

2. 提升系統的辨識速度，若要實際應用於路口監視器必須達到即時辨識，目前 系統架構較複雜導致花費過多時間。

3. 減少車上貼紙廣告造成的錯誤抓取。

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自傳

林永鑫，1994 年出生於臺北市。

 新北市秀朗國小

 臺北市私立東山高級中學 國中部

 臺北市私立東山高級中學

 國立臺灣師範大學電機工程學系

 國立臺灣師範大學電機工程學系研究所

學 術 成 就

 Cheng-Hung Lin, Yong-Sin Lin and Wei-Chen Liu, "An efficient license plate recognition system using convolution neural networks", in Proc. of IEEE International Conference on Applied System Innovation (IEEE ICASI 2018), Chiba, Japan, 13-17 April, 2018.