원문정보
초록
영어
In this paper, the learning technique for CNN processor on vehicle is proposed. In the case of conventional CNN processors, weighted values learned through training are stored for use, but when there is distortion in the image due to the weather conditions, the accuracy is decreased. Therefore, the method of enhancing the input image for classification is general, but it has the weakness of increasing the processor size. To solve this problem, the CNN performance was improved in this paper through the learning method of the distorted image. As a result, the proposed method showed improvement of approximately 38% better accuracy than the conventional method.
목차
1. Introduction
2. Related researches
2.1 Convolutional neural network
2.2 Conventional training method
3. Proposed training method for CNN processor
4. Experiments
5. Conclusion
References
