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Machine Learning in Lung Cancer Radiomics 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 6, 页码: 753-782
作者:  Jiaqi Li;  Zhuofeng Li;  Lei Wei;  Xuegong Zhang
Adobe PDF(7595Kb)  |  收藏  |  浏览/下载：61/14  |  提交时间：2024/04/23
Machine learning, lung cancer, radiomics, medical image, clinical application  
Effective and Robust Detection of Adversarial Examples via Benford-Fourier Coefficients 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 666-682
作者:  Cheng-Cheng Ma;  Bao-Yuan Wu;  Yan-Bo Fan;  Yong Zhang;   Zhi-Feng Li
Adobe PDF(9598Kb)  |  收藏  |  浏览/下载：69/22  |  提交时间：2024/04/23
Adversarial defense, adversarial detection, generalized Gaussian distribution, Benford-Fourier coefficients, image classification  
A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 614-639
作者:  Bolin Gao;  Keke Wan;  Qien Chen;  Zhou Wang;  Rui Li;  Yu Jiang;  Run Mei;  Yinghui Luo;  Keqiang Li
Adobe PDF(12630Kb)  |  收藏  |  浏览/下载：82/23  |  提交时间：2024/04/23
Predictive cruise control (PCC), cloud control system (CCS), cooperative control, efficient operation, intelligent connected vehicle  
Speech Emotion Recognition Using Cascaded Attention Network with Joint Loss for Discrimination of Confusions 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 595-604
作者:  Yang Liu;  Haoqin Sun;  Wenbo Guan;  Yuqi Xia;   Zhen Zhao
Adobe PDF(1966Kb)  |  收藏  |  浏览/下载：48/16  |  提交时间：2024/04/23
Speech emotion recognition (SER), 3-dimensional (3D) feature, cascaded attention network (CAN), triplet loss, joint loss  
Cross-modal Contrastive Learning for Generalizable and Efficient Image-text Retrieval 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 569-582
作者:  Haoyu Lu;  Yuqi Huo;  Mingyu Ding;  Nanyi Fei;  Zhiwu Lu
Adobe PDF(2928Kb)  |  收藏  |  浏览/下载：58/22  |  提交时间：2024/04/23
Image-text retrieval, multimodal modeling, contrastive learning, weak correlation, computer vision  
Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 447-482
作者:  Xiao Wang;  Guangyao Chen;  Guangwu Qian;  Pengcheng Gao;  Xiao-Yong Wei;  Yaowei Wang;  Yonghong Tian;  Wen Gao
Adobe PDF(3540Kb)  |  收藏  |  浏览/下载：73/16  |  提交时间：2024/04/23
Multi-modal (MM), pre-trained model (PTM), information fusion, representation learning, deep learning  
A Survey on Collaborative DNN Inference for Edge Intelligence 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 370-395
作者:  Wei-Qing Ren;  Yu-Ben Qu;  Chao Dong;  Yu-Qian Jing;  Hao Sun;  Qi-Hui Wu;  Song Guo
Adobe PDF(2969Kb)  |  收藏  |  浏览/下载：58/16  |  提交时间：2024/04/23
Artificial intelligence (AI), edge intelligence (EI), distributed computing, deep neural network (DNN), collaborative inference  
Deep Learning-based Moving Object Segmentation: Recent Progress and Research Prospects 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 335-369
作者:  Rui Jiang;  Ruixiang Zhu;  Hu Su;  Yinlin Li;  Yuan Xie;  Wei Zou
Adobe PDF(9061Kb)  |  收藏  |  浏览/下载：55/9  |  提交时间：2024/04/23
Moving object segmentation (MOS), change detection, background subtraction, deep learning (DL), video understanding  
Vision Enhanced Generative Pre-trained Language Model for Multimodal Sentence Summarization 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 2, 页码: 289-298
作者:  Liqiang Jing;  Yiren Li;  Junhao Xu;  Yongcan Yu;  Pei Shen;  Xuemeng Song
Adobe PDF(2389Kb)  |  收藏  |  浏览/下载：54/24  |  提交时间：2024/04/23
Multimodal sentence summarization (MMSS)  generative pre-trained language model (GPLM)  natural language generation  deep learning  artificial intelligence  
Mitigating Spurious Correlations for Self-supervised Recommendation 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 2, 页码: 263-275
作者:  Xin-Yu Lin;  Yi-Yan Xu;  Wen-Jie Wang;  Yang Zhang;  Fu-Li Feng
Adobe PDF(2244Kb)  |  收藏  |  浏览/下载：54/16  |  提交时间：2024/04/23
Self-supervised recommendation  spurious correlations  spurious features  invariant feature learning  contrastive learning