14.5.9.6 Spiking Neural Networks

Chapter Contents (Back)
Neural Networks. Spiking Neural Networks.

Iakymchuk, T.[Taras], Rosado-Munoz, A.[Alfredo], Guerrero-Martinez, J.[Juan], Bataller-Mompean, M.[Manuel], Frances-Villora, J.[Jose],
Simplified spiking neural network architecture and STDP learning algorithm applied to image classification,
JIVP(2015), No. 1, 2015, pp. 4.
DOI Link 1503
BibRef

Cao, Y.Q.[Yong-Qiang], Chen, Y.[Yang], Khosla, D.[Deepak],
Spiking Deep Convolutional Neural Networks for Energy-Efficient Object Recognition,
IJCV(113), No. 1, May 2015, pp. 54-66.
Springer DOI 1506
BibRef

Saleh, A.Y.[Abdulrazak Yahya], Shamsuddin, S.M.[Siti Mariyam], Hamed, H.N.A.[Haza Nuzly Abdull],
A hybrid differential evolution algorithm for parameter tuning of evolving spiking neural network,
IJCVR(7), No. 1/2, 2017, pp. 20-34.
DOI Link 1701
BibRef

Falez, P.[Pierre], Tirilly, P.[Pierre], Bilasco, I.M.[Ioan Marius], Devienne, P.[Philippe], Boulet, P.[Pierre],
Unsupervised visual feature learning with spike-timing-dependent plasticity: How far are we from traditional feature learning approaches?,
PR(93), 2019, pp. 418-429.
Elsevier DOI 1906
Feature learning, Unsupervised learning, Spiking neural networks, Spike-timing dependent plasticity, Image recognition BibRef

Chakraborty, B.[Biswadeep], She, X.[Xueyuan], Mukhopadhyay, S.[Saibal],
A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection,
IP(30), 2021, pp. 9014-9029.
IEEE DOI 2112
Biological neural networks, Object detection, Training, Neurons, Detectors, Standards, Feature extraction, Spiking neural networks, object detection BibRef

Zhang, Z., Liu, Q.,
Spike-Event-Driven Deep Spiking Neural Network With Temporal Encoding,
SPLetters(28), 2021, pp. 484-488.
IEEE DOI 2103
Neurons, Encoding, Feature extraction, Computational modeling, Task analysis, Image coding, Biological neural networks, spiking neural network BibRef

Chen, J.K.[Jian-Kun], Qiu, X.L.[Xiao-Lan], Ding, C.B.[Chi-Biao], Wu, Y.R.[Yi-Rong],
SAR image classification based on spiking neural network through spike-time dependent plasticity and gradient descent,
PandRS(188), 2022, pp. 109-124.
Elsevier DOI 2205
Spiking Neural Network (SNN), SAR image classification, Spike-Time Dependent Plasticity (STDP), Gradient descent BibRef


Jang, H.[Hyeryung], Skatchkovsky, N.[Nicolas], Simeone, O.[Osvaldo],
VOWEL: A Local Online Learning Rule for Recurrent Networks of Probabilistic Spiking Winner- Take-All Circuits,
ICPR21(4597-4604)
IEEE DOI 2105
Training, Neuromorphics, Neurons, Probabilistic logic, Hardware, Timing, Pattern recognition, Neuromorphic Computing BibRef

Barbier, T.[Thomas], Teulière, C.[Céline], Triesch, J.[Jochen],
Spike timing-based unsupervised learning of orientation, disparity, and motion representations in a spiking neural network*,
EventVision21(1377-1386)
IEEE DOI 2109
Visualization, Neuromorphics, Neurons, Detectors, Vision sensors, Robot sensing systems BibRef

Fang, W.[Wei], Yu, Z.F.[Zhao-Fei], Chen, Y.Q.[Yan-Qi], Masquelier, T.[Timothée], Huang, T.J.[Tie-Jun], Tian, Y.H.[Yong-Hong],
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks,
ICCV21(2641-2651)
IEEE DOI 2203
Training, Costs, Power demand, Neuromorphics, Neurons, Manuals, Biomembranes, Computational photography, Recognition and classification BibRef

Garg, I.[Isha], Chowdhury, S.S.[Sayeed Shafayet], Roy, K.[Kaushik],
DCT-SNN: Using DCT to Distribute Spatial Information over Time for Low-Latency Spiking Neural Networks,
ICCV21(4651-4660)
IEEE DOI 2203
Deep learning, Time-frequency analysis, Neurons, Transforms, Encoding, Computational efficiency, Discrete cosine transforms, Vision applications and systems BibRef

Kundu, S.[Souvik], Pedram, M.[Massoud], Beerel, P.A.[Peter A.],
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise,
ICCV21(5189-5198)
IEEE DOI 2203
Training, Costs, Computational modeling, Robustness, Energy efficiency, Reproducibility of results, Emergency Reviewer BibRef

Kundu, S.[Souvik], Datta, G.[Gourav], Pedram, M.[Massoud], Beerel, P.A.[Peter A.],
Spike-Thrift: Towards Energy-Efficient Deep Spiking Neural Networks by Limiting Spiking Activity via Attention-Guided Compression,
WACV21(3952-3961)
IEEE DOI 2106
Training, Machine learning algorithms, Limiting, Firing, Computational modeling, Artificial neural networks, Machine learning BibRef

Han, B.[Bing], Roy, K.[Kaushik],
Deep Spiking Neural Network: Energy Efficiency Through Time Based Coding,
ECCV20(X:388-404).
Springer DOI 2011
BibRef

Sharmin, S.[Saima], Rathi, N.[Nitin], Panda, P.[Priyadarshini], Roy, K.[Kaushik],
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-linear Activations,
ECCV20(XXIX: 399-414).
Springer DOI 2010
BibRef

Han, B., Srinivasan, G., Roy, K.,
RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network,
CVPR20(13555-13564)
IEEE DOI 2008
Training, Biological neural networks, Image recognition, Task analysis, Backpropagation BibRef

Valadez-Godínez, S.[Sergio], González, J.[Javier], Sossa, H.[Humberto],
Efficient Pattern Recognition Using the Frequency Response of a Spiking Neuron,
MCPR17(53-62).
Springer DOI 1706
BibRef

Xiang, Y.[Yande], Meng, J.Y.[Jian-Yi], Ma, D.[De],
A load balanced mapping for spiking neural network,
ICIVC17(899-903)
IEEE DOI 1708
Acceleration, Biology, Handwriting recognition, Neural networks, Quality of service, Sociology, Statistics, NoC, execution time, neural mapping, spiking neural network (SNN). BibRef

Espinal, A.[Andrés], Carpio, M.[Martín], Ornelas, M.[Manuel], Puga, H.[Héctor], Melín, P.[Patricia], Sotelo-Figueroa, M.[Marco],
Developing Architectures of Spiking Neural Networks by Using Grammatical Evolution Based on Evolutionary Strategy,
MCPR14(71-80).
Springer DOI 1407
BibRef

Wysoski, S.G.[Simei Gomes], Benuskova, L.[Lubica], Kasabov, N.[Nikola],
Adaptive Learning Procedure for a Network of Spiking Neurons and Visual Pattern Recognition,
ACIVS06(1133-1142).
Springer DOI 0609
BibRef

Thorpe, S.[Simon],
Ultra-Rapid Scene Categorization with a Wave of Spikes,
BMCV02(1 ff.).
Springer DOI 0303
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Convolutional Neural Networks for Image Descriptions, Classification .


Last update:Aug 14, 2022 at 21:20:19