1. He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep Residual Learning for Image Recognition. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 770–778).
2. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521, 436–444.
3. Han, S., Mao, H., & Dally, W.J. (2015). Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding. arXiv:
abs/1510.00149
.
4. Courbariaux, M., Hubara, I., Soudry, D., El-Yaniv, R., & Bengio, Y. (2016). Binarized neural networks:, Training deep neural networks with weights and activations constrained to+ 1 or-1. arXiv:
1602.02830
.
5. Lee, E.H., Miyashita, D., Chai, E., Murmann, B., & Wong, S.S. (2017). LogNet: Energy-efficient neural networks using logarithmic computation. In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 5900–5904).