Related references
Note: Only part of the references are listed.A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks
Zhaodong Chen et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2022)
Event-Based Vision: A Survey
Guillermo Gallego et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2022)
Attention mechanisms in computer vision: A survey
Meng-Hao Guo et al.
COMPUTATIONAL VISUAL MEDIA (2022)
Progressive Tandem Learning for Pattern Recognition With Deep Spiking Neural Networks
Jibin Wu et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2022)
Rethinking Pretraining as a Bridge From ANNs to SNNs
Yihan Lin et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2022)
Visual explanations from spiking neural networks using inter-spike intervals
Youngeun Kim et al.
SCIENTIFIC REPORTS (2021)
High Speed and High Dynamic Range Video with an Event Camera
Henri Rebecq et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2021)
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks
Wei Fang et al.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021) (2021)
Temporal-wise Attention Spiking Neural Networks for Event Streams Classification
Man Yao et al.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021) (2021)
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks
Bojian Yin et al.
NATURE MACHINE INTELLIGENCE (2021)
Spike-Thrift: Towards Energy-Efficient Deep Spiking Neural Networks by Limiting Spiking Activity via Attention-Guided Compression
Souvik Kundu et al.
2021 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION WACV 2021 (2021)
Optimized spiking neurons can classify images with high accuracy through temporal coding with two spikes
Christoph Stoeckl et al.
NATURE MACHINE INTELLIGENCE (2021)
ViViT: A Video Vision Transformer
Anurag Arnab et al.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021) (2021)
A Simple and Light-Weight Attention Module for Convolutional Neural Networks
Jongchan Park et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2020)
Rethinking the performance comparison between SNNS and ANNS
Lei Deng et al.
NEURAL NETWORKS (2020)
Going Deeper in Spiking Neural Networks: VGG and Residual Architectures
Abhronil Sengupta et al.
FRONTIERS IN NEUROSCIENCE (2019)
Towards artificial general intelligence with hybrid Tianjic chip architecture
Jing Pei et al.
NATURE (2019)
Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-based optimization to spiking neural networks
Emre O. Neftci et al.
IEEE SIGNAL PROCESSING MAGAZINE (2019)
Towards spike-based machine intelligence with neuromorphic computing
Kaushik Roy et al.
NATURE (2019)
EV-Gait: Event-based Robust Gait Recognition using Dynamic Vision Sensors
Yanxiang Wang et al.
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019) (2019)
Loihi: A Neuromorphic Manycore Processor with On-Chip Learning
Mike Davies et al.
IEEE MICRO (2018)
Spatio-Temporal Backpropagation for Training High-Performance Spiking Neural Networks
Yujie Wu et al.
FRONTIERS IN NEUROSCIENCE (2018)
Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva et al.
NATURE (2017)
A Low Power, Fully Event-Based Gesture Recognition System
Arnon Amir et al.
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)
Mastering the game of Go with deep neural networks and tree search
David Silver et al.
NATURE (2016)
Neuronal Mechanisms of Visual Attention
John H. R. Maunsell
ANNUAL REVIEW OF VISION SCIENCE, VOL 1 (2015)
A million spiking-neuron integrated circuit with a scalable communication network and interface
Paul A. Merolla et al.
SCIENCE (2014)
Attention enhances synaptic efficacy and the signal-to-noise ratio in neural circuits
Farran Briggs et al.
NATURE (2013)
Selective Attention and Consciousness: Investigating Their Relation Through Computational Modelling
Kleanthis C. Neokleous et al.
COGNITIVE COMPUTATION (2011)
Communication in neuronal networks
SB Laughlin et al.
SCIENCE (2003)