ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1802.02627
  4. Cited By
Going Deeper in Spiking Neural Networks: VGG and Residual Architectures

Going Deeper in Spiking Neural Networks: VGG and Residual Architectures

7 February 2018
Abhronil Sengupta
Yuting Ye
Robert Y. Wang
Chiao Liu
Kaushik Roy
ArXivPDFHTML

Papers citing "Going Deeper in Spiking Neural Networks: VGG and Residual Architectures"

50 / 291 papers shown
Title
giMLPs: Gate with Inhibition Mechanism in MLPs
Cheng Kang
Jindich Prokop
Lei Tong
Huiyu Zhou
Yong Hu
Daneil Novak
29
0
0
01 Aug 2022
Ultra-low Latency Adaptive Local Binary Spiking Neural Network with
  Accuracy Loss Estimator
Ultra-low Latency Adaptive Local Binary Spiking Neural Network with Accuracy Loss Estimator
Changqin Xu
Yijian Pei
Zili Wu
Yi Liu
Yintang Yang
16
3
0
31 Jul 2022
Text Classification in Memristor-based Spiking Neural Networks
Text Classification in Memristor-based Spiking Neural Networks
Jinqi Huang
A. Serb
S. Stathopoulos
T. Prodromakis
11
14
0
27 Jul 2022
InfiniteNature-Zero: Learning Perpetual View Generation of Natural
  Scenes from Single Images
InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images
Zhengqi Li
Qianqian Wang
Noah Snavely
Angjoo Kanazawa
VGen
34
60
0
22 Jul 2022
Spike Calibration: Fast and Accurate Conversion of Spiking Neural
  Network for Object Detection and Segmentation
Spike Calibration: Fast and Accurate Conversion of Spiking Neural Network for Object Detection and Segmentation
Yang Li
Xiang He
Yiting Dong
Qingqun Kong
Yi Zeng
27
27
0
06 Jul 2022
How Far Can I Go ? : A Self-Supervised Approach for Deterministic Video
  Depth Forecasting
How Far Can I Go ? : A Self-Supervised Approach for Deterministic Video Depth Forecasting
Suaradip Nag
Nisarg A. Shah
Anran Qi
Raghavendra Ramachandra
MDE
24
2
0
01 Jul 2022
Examining the Robustness of Spiking Neural Networks on Non-ideal
  Memristive Crossbars
Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars
Abhiroop Bhattacharjee
Youngeun Kim
Abhishek Moitra
Priyadarshini Panda
30
15
0
20 Jun 2022
SNN2ANN: A Fast and Memory-Efficient Training Framework for Spiking
  Neural Networks
SNN2ANN: A Fast and Memory-Efficient Training Framework for Spiking Neural Networks
Jianxiong Tang
Jianhuang Lai
Xiaohua Xie
Lingxiao Yang
Weimin Zheng
13
13
0
19 Jun 2022
Spiking Neural Networks for Frame-based and Event-based Single Object
  Localization
Spiking Neural Networks for Frame-based and Event-based Single Object Localization
Sami Barchid
José Mennesson
J. Eshraghian
Chaabane Djéraba
Bennamoun
35
29
0
13 Jun 2022
A Synapse-Threshold Synergistic Learning Approach for Spiking Neural
  Networks
A Synapse-Threshold Synergistic Learning Approach for Spiking Neural Networks
Hongze Sun
Wuque Cai
Baoxin Yang
Yan Cui
Yang Xia
D. Yao
Daqing Guo
41
13
0
10 Jun 2022
SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection
  for Autonomous Driving
SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving
S. Mohapatra
Thomas Mesquida
Mona Hodaei
S. Yogamani
H. Gotzig
Patrick Mäder
3DPC
39
1
0
06 Jun 2022
A Resource-efficient Spiking Neural Network Accelerator Supporting
  Emerging Neural Encoding
A Resource-efficient Spiking Neural Network Accelerator Supporting Emerging Neural Encoding
Daniel Gerlinghoff
Zhehui Wang
Xiaozhe Gu
Rick Siow Mong Goh
Yaoyu Zhang
17
8
0
06 Jun 2022
Linear Leaky-Integrate-and-Fire Neuron Model Based Spiking Neural
  Networks and Its Mapping Relationship to Deep Neural Networks
Linear Leaky-Integrate-and-Fire Neuron Model Based Spiking Neural Networks and Its Mapping Relationship to Deep Neural Networks
Si-wei Lu
Fengyi Xu
25
23
0
31 May 2022
Efficient Federated Learning with Spike Neural Networks for Traffic Sign
  Recognition
Efficient Federated Learning with Spike Neural Networks for Traffic Sign Recognition
Kan Xie
Zhe Zhang
Bo Li
Jiawen Kang
Dusit Niyato
Shengli Xie
Yi Wu
25
67
0
28 May 2022
2D versus 3D Convolutional Spiking Neural Networks Trained with
  Unsupervised STDP for Human Action Recognition
2D versus 3D Convolutional Spiking Neural Networks Trained with Unsupervised STDP for Human Action Recognition
Mireille el Assal
Pierre Tirilly
Ioan Marius Bilasco
3DH
16
5
0
26 May 2022
Memory-enriched computation and learning in spiking neural networks
  through Hebbian plasticity
Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity
Thomas Limbacher
Ozan Özdenizci
Robert Legenstein
21
2
0
23 May 2022
Spiking Neural Operators for Scientific Machine Learning
Spiking Neural Operators for Scientific Machine Learning
Adar Kahana
Qian Zhang
Leonard Gleyzer
George Karniadakis
34
9
0
17 May 2022
Spiking Approximations of the MaxPooling Operation in Deep SNNs
Spiking Approximations of the MaxPooling Operation in Deep SNNs
Ramashish Gaurav
B. Tripp
Apurva Narayan
40
8
0
14 May 2022
Programming molecular systems to emulate a learning spiking neuron
Programming molecular systems to emulate a learning spiking neuron
Jakub Fil
Neil Dalchau
Dominique F. Chu
6
6
0
09 May 2022
Converting Artificial Neural Networks to Spiking Neural Networks via
  Parameter Calibration
Converting Artificial Neural Networks to Spiking Neural Networks via Parameter Calibration
Yuhang Li
Shi-Wee Deng
Xin Dong
Shi Gu
59
24
0
06 May 2022
Training High-Performance Low-Latency Spiking Neural Networks by
  Differentiation on Spike Representation
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation
Qingyan Meng
Mingqing Xiao
Shen Yan
Yisen Wang
Zhouchen Lin
Zhimin Luo
24
134
0
01 May 2022
Efficient and Accurate Conversion of Spiking Neural Network with Burst
  Spikes
Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes
Yang Li
Yi Zeng
27
57
0
28 Apr 2022
MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and
  Plasticity into Bio-Plausible Spiking Neural Networks
MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks
Chengting Yu
Yang-Guang Du
Mufeng Chen
Aili Wang
Gaoang Wang
Erping Li
AAML
35
3
0
21 Apr 2022
Brain-inspired Multilayer Perceptron with Spiking Neurons
Brain-inspired Multilayer Perceptron with Spiking Neurons
Wenshuo Li
Hanting Chen
Jianyuan Guo
Ziyang Zhang
Yunhe Wang
35
35
0
28 Mar 2022
Efficient Hardware Acceleration of Sparsely Active Convolutional Spiking
  Neural Networks
Efficient Hardware Acceleration of Sparsely Active Convolutional Spiking Neural Networks
Jan Sommer
M. A. Özkan
Oliver Keszocze
Jürgen Teich
9
18
0
23 Mar 2022
Recent Advances and New Frontiers in Spiking Neural Networks
Recent Advances and New Frontiers in Spiking Neural Networks
Duzhen Zhang
Shuncheng Jia
Qingyu Wang
AAML
AI4CE
21
23
0
12 Mar 2022
Rethinking the role of normalization and residual blocks for spiking
  neural networks
Rethinking the role of normalization and residual blocks for spiking neural networks
Shin-ichi Ikegawa
Ryuji Saiin
Yoshihide Sawada
N. Natori
21
17
0
03 Mar 2022
Rethinking Pretraining as a Bridge from ANNs to SNNs
Rethinking Pretraining as a Bridge from ANNs to SNNs
Yihan Lin
Yifan Hu
Shiji Ma
Guo-Qi Li
Dongjie Yu
42
12
0
02 Mar 2022
Temporal Efficient Training of Spiking Neural Network via Gradient
  Re-weighting
Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting
Shi-Wee Deng
Yuhang Li
Shanghang Zhang
Shi Gu
133
250
0
24 Feb 2022
Energy-Efficient Respiratory Anomaly Detection in Premature Newborn
  Infants
Energy-Efficient Respiratory Anomaly Detection in Premature Newborn Infants
A. Paul
Md. Abu Saleh Tajin
Anup Das
W. Mongan
K. Dandekar
35
11
0
21 Feb 2022
Optimized Potential Initialization for Low-latency Spiking Neural
  Networks
Optimized Potential Initialization for Low-latency Spiking Neural Networks
Tong Bu
Jianhao Ding
Zhaofei Yu
Tiejun Huang
106
89
0
03 Feb 2022
AutoSNN: Towards Energy-Efficient Spiking Neural Networks
AutoSNN: Towards Energy-Efficient Spiking Neural Networks
Byunggook Na
J. Mok
Seongsik Park
Dongjin Lee
Hyeokjun Choe
Sungroh Yoon
50
63
0
30 Jan 2022
Neural Architecture Search for Spiking Neural Networks
Neural Architecture Search for Spiking Neural Networks
Youngeun Kim
Yuhang Li
Hyoungseob Park
Yeshwanth Venkatesha
Priyadarshini Panda
26
88
0
23 Jan 2022
Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking
  Neural Networks?
Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking Neural Networks?
Gourav Datta
P. Beerel
46
37
0
22 Dec 2021
Advancing Spiking Neural Networks towards Deep Residual Learning
Advancing Spiking Neural Networks towards Deep Residual Learning
Yifan Hu
Lei Deng
Yujie Wu
Man Yao
Guoqi Li
21
86
0
15 Dec 2021
Human-Level Control through Directly-Trained Deep Spiking Q-Networks
Human-Level Control through Directly-Trained Deep Spiking Q-Networks
Guisong Liu
Wenjie Deng
Xiurui Xie
Li Huang
Huajin Tang
OffRL
27
43
0
13 Dec 2021
Efficient Training of Spiking Neural Networks with Temporally-Truncated
  Local Backpropagation through Time
Efficient Training of Spiking Neural Networks with Temporally-Truncated Local Backpropagation through Time
Wenzhe Guo
M. Fouda
A. Eltawil
K. Salama
28
12
0
13 Dec 2021
Advancing Deep Residual Learning by Solving the Crux of Degradation in Spiking Neural Networks
Yifan Hu
Yujie Wu
Lei Deng
Guoqi Li
30
5
0
09 Dec 2021
Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for
  Event-Based Vision
Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision
Alexander Kugele
Thomas Pfeil
Michael Pfeiffer
Elisabetta Chicca
42
30
0
06 Dec 2021
Direct Training via Backpropagation for Ultra-low Latency Spiking Neural
  Networks with Multi-threshold
Direct Training via Backpropagation for Ultra-low Latency Spiking Neural Networks with Multi-threshold
Changqin Xu
Yi Liu
Yintang Yang
20
12
0
25 Nov 2021
Design of Many-Core Big Little μBrain for Energy-Efficient Embedded
  Neuromorphic Computing
Design of Many-Core Big Little μBrain for Energy-Efficient Embedded Neuromorphic Computing
M. L. Varshika
Adarsha Balaji
Federico Corradi
Anup Das
J. Stuijt
F. Catthoor
30
25
0
23 Nov 2021
E3NE: An End-to-End Framework for Accelerating Spiking Neural Networks
  with Emerging Neural Encoding on FPGAs
E3NE: An End-to-End Framework for Accelerating Spiking Neural Networks with Emerging Neural Encoding on FPGAs
Daniel Gerlinghoff
Zhehui Wang
Xiaozhe Gu
Rick Siow Mong Goh
Yaoyu Zhang
19
23
0
19 Nov 2021
L4-Norm Weight Adjustments for Converted Spiking Neural Networks
L4-Norm Weight Adjustments for Converted Spiking Neural Networks
Jason M. Allred
Kaushik Roy
20
2
0
17 Nov 2021
Keys to Accurate Feature Extraction Using Residual Spiking Neural
  Networks
Keys to Accurate Feature Extraction Using Residual Spiking Neural Networks
Alex Vicente-Sola
D. L. Manna
Paul Kirkland
G. D. Caterina
Trevor Bihl University of Strathclyde
25
22
0
10 Nov 2021
An Adaptive Sampling and Edge Detection Approach for Encoding Static
  Images for Spiking Neural Networks
An Adaptive Sampling and Edge Detection Approach for Encoding Static Images for Spiking Neural Networks
Peyton S. Chandarana
Jun Ou
Ramtin Zand
23
4
0
19 Oct 2021
Backpropagation with Biologically Plausible Spatio-Temporal Adjustment
  For Training Deep Spiking Neural Networks
Backpropagation with Biologically Plausible Spatio-Temporal Adjustment For Training Deep Spiking Neural Networks
Guobin Shen
Dongcheng Zhao
Yi Zeng
41
54
0
17 Oct 2021
Beyond Classification: Directly Training Spiking Neural Networks for
  Semantic Segmentation
Beyond Classification: Directly Training Spiking Neural Networks for Semantic Segmentation
Youngeun Kim
Joshua Chough
Priyadarshini Panda
48
80
0
14 Oct 2021
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep
  Spiking Neural Networks by Training with Crafted Input Noise
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise
Souvik Kundu
Massoud Pedram
P. Beerel
AAML
22
71
0
06 Oct 2021
One Timestep is All You Need: Training Spiking Neural Networks with
  Ultra Low Latency
One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency
Sayeed Shafayet Chowdhury
Nitin Rathi
Kaushik Roy
23
40
0
01 Oct 2021
Spiking Hyperdimensional Network: Neuromorphic Models Integrated with
  Memory-Inspired Framework
Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework
Zhuowen Zou
H. Alimohamadi
Farhad Imani
Yeseong Kim
Mohsen Imani
36
19
0
01 Oct 2021
Previous
123456
Next