Fine-Grained Vehicle Classification in Urban Traffic Scenes Using Deep Learning-Reference-Cited by-同舟云学术

Fine-Grained Vehicle Classification in Urban Traffic Scenes Using Deep Learning

Published:2022 Issue: Volume: Page:902-908
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Najeeb Syeda Aneeba,Raza Rana Hammad,Yusuf Adeel,Sultan Zamra

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-8129-5_138

Reference16 articles.

1. Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. Adv. Neural. Inf. Process. Syst. 25, 1097–1105 (2012)

2. Szegedy, C., et al.: Going deeper with convolutions. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–9, June 2015

3. He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770–778, June 2016

4. Xie, S., Sun, C., Huang, J., Tu, Z., Murphy, K.: Rethinking the inception architecture for computer vision. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2818–2826, June 2016

5. Iandola, F.N., Han, S., Moskewicz, M.W., Ashraf, K., Dally, W.J., Keutzer, K.: SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5 MB model size arXiv preprint arXiv:1602.07360 (2016)

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