IIAE CONFERENCE SYSTEM, The 5th IIAE International Conference on Industrial Application Engineering 2017 (ICIAE2017)

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Recognition of Road in Bad Weather Using Deep Learning
Yu Nakagawa, Huimin Lu, Kenta Kagemoto, Nobuhiro Hirano, Shiyuan Yang, Seiichi Serikawa

Last modified: 2017-02-22

Abstract


Although the development and research of automatic driving has advanced in recent years, it has not yet been realized. We think that recognition of objects is necessary to make automated driving practical. It is necessary to grasp the course regardless of the weather. Use deep learning to recognize objects. We use CNN which is suitable for image recognition even in depth learning. Recognition of objects during rainy weather has not yet been realized, and it is necessary to create that database. Creating databases photographs the roads themselves and collects many databases. Make sure that the road in various situations can be recognized as a road. Then, it learns the database by deep learning and identifies whether it can be recognized as a road.

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