Photonic integrated neuro-synaptic core for convolutional spiking neural network [PDF]
Opto-Electronic Advances, 2023 Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture. Linear weighting and nonlinear spiking activation are two fundamental functions of a photonic spiking neural ...
Dianzhuang Zheng
exaly +2 more sources
Spiking Neural Network Based on Multi-Scale Saliency Fusion for Breast Cancer Detection
Entropy, 2022 Deep neural networks have been successfully applied in the field of image recognition and object detection, and the recognition results are close to or even superior to those from human beings.
Qiang Fu, Hongbin Dong
doaj +3 more sources
Backpropagation With Sparsity Regularization for Spiking Neural Network Learning
Frontiers in Neuroscience, 2022 The spiking neural network (SNN) is a possible pathway for low-power and energy-efficient processing and computing exploiting spiking-driven and sparsity features of biological systems.
Lirong Zheng, Zhuo Zou, Yuxiang Huan
exaly +2 more sources
Study and Evaluation of Spiking Neural Network Model Based on Bee Colony Optimization [PDF]
Jisuanji kexue, 2023 In order to improve the training ability of Spiking neural network,this paper takes multi-label classification problem as the research breakthrough point and adopts bee colony algorithm to optimize the model.There are many neural network models based on ...
MA Weiwei, ZHENG Qinhong, LIU Shanshan
doaj +1 more source
Combinatorial optimization solving by coherent Ising machines based on spiking neural networks [PDF]
Quantum, 2023 Spiking neural network is a kind of neuromorphic computing that is believed to improve the level of intelligence and provide advantages for quantum computing.
Bo Lu, Yong-Pan Gao, Kai Wen, Chuan Wang
doaj +1 more source
Spikformer: When Spiking Neural Network Meets Transformer [PDF]
International Conference on Learning Representations, 2022 We consider two biologically plausible structures, the Spiking Neural Network (SNN) and the self-attention mechanism. The former offers an energy-efficient and event-driven paradigm for deep learning, while the latter has the ability to capture feature ...
Zhaokun Zhou +6 more
semanticscholar +1 more source
Spiking Neural Network Model for Brain-like Computing and Progress of Its Learning Algorithm [PDF]
Jisuanji kexue, 2023 With the increasingly prominent limitations of deep neural networks in practical applications,brain-like computing spiking neural networks with biological interpretability have become the focus of research.The uncertainty and complex diversity of ...
HUANG Zenan, LIU Xiaojie, ZHAO Chenhui, DENG Yabin, GUO Donghui
doaj +1 more source
Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANN [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 Spiking neural networks (SNNs) have shown advantages in computation and energy efficiency over traditional artificial neural networks (ANNs) thanks to their event-driven representations.
Yang-Zhi Hu +3 more
semanticscholar +1 more source
DYNAP-SE2: a scalable multi-core dynamic neuromorphic asynchronous spiking neural network processor [PDF]
Neuromorph. Comput. Eng., 2023 With the remarkable progress that technology has made, the need for processing data near the sensors at the edge has increased dramatically. The electronic systems used in these applications must process data continuously, in real-time, and extract ...
Ole Richter +6 more
semanticscholar +1 more source
Event-based Video Reconstruction via Potential-assisted Spiking Neural Network [PDF]
Computer Vision and Pattern Recognition, 2022 Neuromorphic vision sensor is a new bio-inspired imaging paradigm that reports asynchronous, continuously perpixel brightness changes called ‘events’ with high temporal resolution and high dynamic range.
Lin Zhu +5 more
semanticscholar +1 more source