Results 231 to 240 of about 7,211,078 (250)

A survey of approaches for implementing optical neural networks

, 2021
Conventional neural networks are software simulations of artificial neural networks (ANNs) implemented on von Neumann machines. This technology has recently encountered bottlenecks in terms of computing speed and energy consumption, leading to increased ...
Run-Qin Xu, Pin Lv, Fan-Jiang Xu, Yishi Shi   +3 more
semanticscholar   +1 more source

A Comparative Study between Artificial Neural Networks and Optical Neural Networks

2022 4th International Conference on Current Research in Engineering and Science Applications (ICCRESA), 2022
Artificial intelligence has gained widespread interest from people from all walks of life since the big data era arrived, so artificial neural networks (ANNs) are one of the most important areas of artificial intelligence that have a close relationship ...
Zainab Faris, I. Murdas
semanticscholar   +1 more source

SqueezeLight: Towards Scalable Optical Neural Networks with Multi-Operand Ring Resonators

Design, Automation and Test in Europe, 2021
Optical neural networks (ONNs) have demonstrated promising potentials for next-generation artificial intelligence acceleration with ultra-low latency, high bandwidth, and low energy consumption.
Jiaqi Gu, Chenghao Feng, Zheng Zhao, Zhoufeng Ying, Mingjie Liu, Ray T. Chen, David Z. Pan   +6 more
semanticscholar   +1 more source

Towards Area-Efficient Optical Neural Networks: An FFT-based Architecture

Asia and South Pacific Design Automation Conference, 2020
As a promising neuromorphic framework, the optical neural network (ONN) demonstrates ultra-high inference speed with low energy consumption. However, the previous ONN architectures have high area overhead which limits their practicality.
Jiaqi Gu, Zheng Zhao, Chenghao Feng, Mingjie Liu, Ray T. Chen, David Z. Pan   +5 more
semanticscholar   +1 more source

ROQ: A Noise-Aware Quantization Scheme Towards Robust Optical Neural Networks with Low-bit Controls

Design, Automation and Test in Europe, 2020
Optical neural networks (ONNs) demonstrate orders-of-magnitude higher speed in deep learning acceleration than their electronic counterparts. However, limited control precision and device variations induce accuracy degradation in practical ONN ...
Jiaqi Gu, Zheng Zhao, Chenghao Feng, Hanqing Zhu, Ray T. Chen, David Z. Pan   +5 more
semanticscholar   +1 more source

Metasurface-Based Optical Neural Network and its Application in Next-Generation Optical Communications and Networks

Journal of Lightwave Technology
Optical neural network (ONN), integrating deep learning algorithms and optical computing (OC) hardware, are gradually emerging as a powerful tool for artificial intelligence (AI) computing.
Chenguang Rong, Lin Wu, Jin Tao, Yong-Zhi Cheng, Kai-Yuan Wang, Lin Chen, Hui Luo, Fu Chen, Xiang-Cheng Li   +8 more
semanticscholar   +1 more source

Light in AI: Toward Efficient Neurocomputing With Optical Neural Networks—A Tutorial

IEEE Transactions on Circuits and Systems - II - Express Briefs, 2022
Jiaqi Gu, Chenghao Feng, Hanqing Zhu, Ray T. Chen, David Z. Pan   +4 more
semanticscholar   +1 more source

All-optical computing based on convolutional neural networks

Opto-Electronic Advances, 2021
Hongtao Lin, Cuicui Lu, Xiaoyong Hu
exaly  

Toward Hardware-Efficient Optical Neural Networks: Beyond FFT Architecture via Joint Learnability

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2021
Jiaqi Gu, Zheng Zhao, Chenghao Feng, Zhoufeng Ying, Mingjie Liu, Ray T. Chen, David Z. Pan   +6 more
semanticscholar   +1 more source

Backpropagation through nonlinear units for the all-optical training of neural networks

Photonics Research, 2021
Thomas Barrett, Guo Xianxin, Alexander Lvovsky   +2 more
exaly