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PP-NAS: Searching for Plug-and-Play Blocks on Convolutional Neural Networks 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13
作者:  Xiao, Anqi;  Shen, Biluo;  Tian, Jie;  Hu, Zhenhua
收藏  |  浏览/下载:77/0  |  提交时间:2023/11/17
Convolution  Search problems  Optimization  Computer architecture  Object detection  Molecular imaging  Visualization  Multiscale  neural architecture search (NAS)  plug-and-play  representation learning  
Chest Radiographs Using a Context-Fusion Convolution Neural Network (CNN): Can It Distinguish the Etiology of Community-Acquired Pneumonia (CAP) in Children? 期刊论文
JOURNAL OF DIGITAL IMAGING, 2022, 页码: 12
作者:  Hu, Shasha;  Zhu, Yongbei;  Dong, Di;  Wang, Bei;  Zhou, Zuofu;  Wang, Chi;  Tian, Jie;  Peng, Yun
收藏  |  浏览/下载:206/0  |  提交时间:2022/07/25
Chest radiographs  Convolution neural network  Community-acquired pneumonia  Pediatric  Etiology  
graph convolution based residual connected network for morphological reconstruction in fluorescence molecular tomography 会议论文
, 美国, 2022-2
作者:  Wang Y(王宇);  Bian C(边畅);  Du Y(杜洋);  Tian J(田捷)
Adobe PDF(625Kb)  |  收藏  |  浏览/下载:184/56  |  提交时间:2022/06/14
Fluorescence molecular tomography  Graph convolution network  
Cascaded one-shot deformable convolutional neural networks: Developing a deep learning model for respiratory motion estimation in ultrasound sequences 期刊论文
Medical Image Analysis, 2020, 卷号: 65, 期号: 65, 页码: 101793
作者:  Fei Liu;  Dan Liu;  Jie Tian;  Xiaoyan Xie;  Xin Yang;  Wang K(王坤)
浏览  |  Adobe PDF(3180Kb)  |  收藏  |  浏览/下载:192/56  |  提交时间:2020/11/02
Ultrasound sequence  Respiratory motion estimation  Cascaded Siamese network  One-shot deformable convolution  
Fast and Robust Reconstruction Method for Fluorescence Molecular Tomography based on Deep Neural Network 会议论文
, The Moscone Center, San Francisco, California, USA, 2019-02-02
作者:  Huang C(黄超);  Meng Hui;  Yuan Gao;  Shixin Jiang;  Kun Wang;  Jie Tian
浏览  |  Adobe PDF(587Kb)  |  收藏  |  浏览/下载:361/147  |  提交时间:2019/04/29
Fluorescence Molecular Tomography, Ill-poseness, Deep Convolution Neural Network, Reconstruction.