Vehicle type classification using an enhanced sparse-filtered convolutional neural network with layer-skipping strategy
In this paper, a vehicle type classification approach is proposed by using an enhanced feature extraction technique based on Sparse-Filtered Convolutional Neural Network with Layer-Skipping strategy (SF-CNNLS). To extract rich and discriminant vehicle features, we introduce Three-Channels of SF-CNNL...
| Автори: | , , |
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| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
IEEE
2020
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| Предмети: | |
| Онлайн доступ: | http://umpir.ump.edu.my/id/eprint/30744/8/Vehicle%20Type%20Classification%20Using%20an%20Enhanced%20Sparse-Filtered%20Convolutional%20Neural%20Network%20with%20Layer-Skipping%20Strategy.pdf |