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Symmetric-threshold ReLU for Fast and Nearly Lossless ANN-SNN Conversion 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 435-446
作者:  Jianing Han;  Ziming Wang;  Jiangrong Shen;  Huajin Tang
Adobe PDF(1513Kb)  |  收藏  |  浏览/下载：52/19  |  提交时间：2024/04/23
Symmetric-threshold rectified linear unit (stReLU), deep spiking neural networks, artificial neural network-spiking neural network (ANN-SNN) conversion, lossless conversion, double thresholds  
Efficient Visual Recognition: A Survey on Recent Advances and Brain-inspired Methodologies 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 5, 页码: 366-411
作者:  Yang Wu;  Ding-Heng Wang;  Xiao-Tong Lu;  Fan Yang;  Man Yao;  Wei-Sheng Dong;  Jian-Bo Shi;  Guo-Qi Li
Adobe PDF(6780Kb)  |  收藏  |  浏览/下载：52/8  |  提交时间：2024/04/23
Visual recognition  deep neural networks (DNNS)  brain-inspired methodologies  network compression  dynamic inference  survey  
A Novel Attention-based Global and Local Information Fusion Neural Network for Group Recommendation 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 4, 页码: 331-346
作者:  Song Zhang;  Nan Zheng;  Dan-Li Wang
Adobe PDF(1317Kb)  |  收藏  |  浏览/下载：34/14  |  提交时间：2024/04/23
Group recommendation  attentive neural network (ANN)  global information  local information  recommender system  
Image De-occlusion via Event-enhanced Multi-modal Fusion Hybrid Network 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 4, 页码: 307-318
作者:  Si-Qi Li;  Yue Gao;  Qiong-Hai Dai
Adobe PDF(4505Kb)  |  收藏  |  浏览/下载：54/15  |  提交时间：2024/04/23
Event camera  multi-modal fusion  image de-occlusion  spiking neural network (SNN)  image reconstruction  
A Framework for Distributed Semi-supervised Learning Using Single-layer Feedforward Networks 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 1, 页码: 63-74
作者:  Jin Xie;  San-Yang Liu;  Jia-Xi Chen
Adobe PDF(1245Kb)  |  收藏  |  浏览/下载：53/23  |  提交时间：2024/04/23
Distributed learning (DL)  semi-supervised learning (SSL)  manifold regularization (MR)  single layer feed-forward neural network (SLFNN)  privacy preserving