Compression and Speed-up of Convolutional Neural Networks Through Dimensionality Reduction for Efficient Inference on Embedded Multiprocessor

Author:

Fernández Brillet Lucas,Leclaire Nicolas,Mancini Stéphane,Nicolas Marina,Cleyet-Merle Sébastien,Henriques Jean-Paul,Delnondedieu Claude

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Modelling and Simulation,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering

Reference42 articles.

1. Krizhevsky, A., Sutskever, I., & Hinton, G.E. (2012). Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. pp 1097–1105.

2. Shlens, J. (2014). A tutorial on principal component analysis. arXiv:1404.1100.

3. Canziani, A., Adam P., & Eugenio C. (2016). An analysis of deep neural network models for practical applications. arXiv:1605.07678.

4. Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. In Proceedings of international conference on learning representations.

5. He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition. pp 770–778.

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