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Cogeneration of Innovative Audio-visual Content: A New Challenge for Computing Art 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 1, 页码: 4-28
作者:  Mengting Liu;  Ying Zhou;  Yuwei Wu;  Feng Gao
Adobe PDF(14438Kb)  |  收藏  |  浏览/下载：1/0  |  提交时间：2024/04/23
Artificial intelligence (AI) art, audio-visual, artificial intelligence generated content (AIGC), multimodal, artistic evaluation  
Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 6, 页码: 822-836
作者:  Kai Zhang;  Yawei Li;  Jingyun Liang;  Jiezhang Cao;  Yulun Zhang;  Hao Tang;  Deng-Ping Fan;  Radu Timofte;  Luc Van Gool
Adobe PDF(7952Kb)  |  收藏  |  浏览/下载：2/1  |  提交时间：2024/04/23
Blind image denoising, real image denosing data synthesis, Transformer, image signal processing (ISP) pipeline  
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：5/0  |  提交时间：2024/04/23
Visual recognition  deep neural networks (DNNS)  brain-inspired methodologies  network compression  dynamic inference  survey  
Denoised Internal Models: A Brain-inspired Autoencoder Against Adversarial Attacks 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 5, 页码: 456-471
作者:  Kai-Yuan Liu;  Xing-Yu Li;  Yu-Rui Lai;  Hang Su;  Jia-Chen Wang;  Chun-Xu Guo;  Hong Xie;  Ji-Song Guan;  Yi Zhou
Adobe PDF(3203Kb)  |  收藏  |  浏览/下载：0/0  |  提交时间：2024/04/23
Brain-inspired learning  autoencoder  robustness  adversarial attack  generative model  
Knowledge Mining: A Cross-disciplinary Survey 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 2, 页码: 89-114
作者:  Yong Rui;  Vicente Ivan Sanchez Carmona;  Mohsen Pourvali;  Yun Xing;  Wei-Wen Yi;  Hui-Bin Ruan;  Yu Zhang
Adobe PDF(1635Kb)  |  收藏  |  浏览/下载：6/1  |  提交时间：2024/04/23
Knowledge mining  knowledge extraction  information extraction  association rule  interpretability