Quantization Effects on a Convolutional Layer of a Deep Neural Network

Author:

Swati ,Verma Dheeraj,Prajapati Jigna,Engineer Pinalkumar

Publisher

Springer Nature Singapore

Reference15 articles.

1. Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Proceedings of the 25th International Conference on Neural Information Processing Systems, vol. 1 (NIPS12)pp. 1097–1105. Curran Associates Inc., Red Hook, NY, USA (2012)

2. Han, S., Pool, J., Tran, J., Dally, W.: Learning both weights and connections for efficient neural network. In: Advances in Neural Information Processing Systems, pp. 1135–1143 (2015)

3. Han, S., Mao, H., Dally, W.J.: Deep compression: compressing deep neural network with pruning, trained quantization and Huffman coding. Comput. Vis. Pattern Recogn. (2015)

4. Dally, W.: High-performance hardware for machine learning. In: Tutorial in Advances in Neural Information Processing Systems (2015)

5. Jacob, B., Kligys, S., Chen, B., Zhu, M., Tang, M., Howard, A., Adam, H., Kalenichenko, D.: Quantization and training of neural networks for efficient integer-arithmetic-only inference (2017)

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