Photonics Research, Volume. 11, Issue 2, 299(2023)
Optical multi-imaging–casting accelerator for fully parallel universal convolution computing
[2] A. Krizhevsky, I. Sutskever, G. E. Hinton. ImageNet classification with deep convolutional neural networks. Adv. Neural Inf. Process. Syst., 25, 1097-1105(2013).
[4] J. Cong, B. Xiao. Minimizing computation in convolutional neural networks. International Conference on Artificial Neural Networks, 281-290(2014).
[6] Y. Ito, R. Matsumiya, T. Endo. OOC-cuDNN: accommodating convolutional neural networks over GPU memory capacity. IEEE International Conference on Big Data, 183-192(2017).
[7] K. He, X. Zhang, S. Ren, J. Sun. Deep residual learning for image recognition. IEEE Conference on Computer Vision and Pattern Recognition, 770-778(2016).
[10] P. Ambs. Optical computing: a 60-year adventure. Adv. Opt. Photon., 2010, 1-15(2010).
[11] A. Maréchal, P. Croce. Un filtre de fréquences spatiales pour l’amélioration du contraste des images optiques. C. R. Acad. Sci., 237(1953).
[13] P. R. Prucnal, B. J. Shastri. Neuromorphic Photonics(2017).
Get Citation
Copy Citation Text
Guoqing Ma, Junjie Yu, Rongwei Zhu, Changhe Zhou, "Optical multi-imaging–casting accelerator for fully parallel universal convolution computing," Photonics Res. 11, 299 (2023)
Category: Instrumentation and Measurements
Received: Aug. 8, 2022
Accepted: Dec. 20, 2022
Published Online: Feb. 8, 2023
The Author Email: Changhe Zhou (chazhou@mail.shcnc.ac.cn)