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GRAMO: geometric resampling augmentation for monocular 3D object detection 期刊论文
FRONTIERS OF COMPUTER SCIENCE, 2024, 卷号: 18, 期号: 5, 页码: 9
作者:  Guan, He;  Song, Chunfeng;  Zhang, Zhaoxiang
Adobe PDF(2242Kb)  |  收藏  |  浏览/下载：104/3  |  提交时间：2024/02/21
3D detection  monocular  augmentation  geometry  
Development and Validation of a Deep Learning Model to Screen for Trisomy 21 During the First Trimester From Nuchal Ultrasonographic Images 期刊论文
JAMA NETWORK OPEN, 2022, 卷号: 5, 期号: 6, 页码: 11
作者:  Zhang, Liwen;  Dong, Di;  Sun, Yongqing;  Hu, Chaoen;  Sun, Congxin;  Wu, Qingqing;  Tian, Jie
Adobe PDF(1293Kb)  |  收藏  |  浏览/下载：279/15  |  提交时间：2022/07/25
Hardware-Oriented Algorithm for High-Speed Laser Centerline Extraction Based on Hessian Matrix 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 卷号: 70, 页码: 14
作者:  Li, Zhikai;  Ma, Liping;  Long, Xianlei;  Chen, Yunze;  Deng, Haitao;  Yan, Fengxia;  Gu, Qingyi
Adobe PDF(3764Kb)  |  收藏  |  浏览/下载：332/51  |  提交时间：2022/03/17
Hardware image processing  Hessian matrix  high-speed vision  laser centerline extraction  line-section 3-D reconstruction  
Progressive polarization based reflection removal via realistic training data generation 期刊论文
PATTERN RECOGNITION, 2022, 卷号: 124, 页码: 13
作者:  Pang, Youxin;  Yuan, Mengke;  Fu, Qiang;  Ren, Peiran;  Yan, Dong-Ming
Adobe PDF(4985Kb)  |  收藏  |  浏览/下载：343/47  |  提交时间：2022/02/16
Deep learning  Reflection removal  Polarization  Progressive network  Convolutional neural networks  
Cross-Modality Synergy Network for Referring Expression Comprehension and Segmentation 期刊论文
Neurocomputing, 2022, 卷号: 467, 期号: /, 页码: 99-114
作者:  Li, Qianzhong;  Zhang, Yujia;  Sun, Shiying;  Wu, Jinting;  Zhao, Xiaoguang;  Tan, Min
Adobe PDF(4555Kb)  |  收藏  |  浏览/下载：360/58  |  提交时间：2021/12/28
Referring expression comprehension  Referring expression segmentation  Cross-modality synergy  Attention mechanism  
Transformers in computational visual media: A survey 期刊论文
Computational Visual Media, 2021, 卷号: 8, 期号: 1, 页码: 33-62
作者:  Xu,Yifan;  Wei,Huapeng;  Lin,Minxuan;  Deng,Yingying;  Sheng,Kekai;  Zhang,Mengdan;  Tang,Fan;  Dong,Weiming;  Huang,Feiyue;  Xu,Changsheng
Adobe PDF(5366Kb)  |  收藏  |  浏览/下载：330/47  |  提交时间：2021/12/28
visual transformer  computational visual media (CVM)  high-level vision  low-level vision  image generation  multi-modal learning  
Rethinking semantic-visual alignment in zero-shot object detection via a softplus margin focal loss 期刊论文
Neurocomputing, 2021, 卷号: 449, 页码: 117-135
作者:  Li, Qianzhong;  Zhang, Yujia;  Sun, Shiying;  Zhao, Xiaoguang;  Li, Kang;  Tan, Min
Adobe PDF(8753Kb)  |  收藏  |  浏览/下载：330/49  |  提交时间：2021/08/15
Zero-shot object detection  Softplus margin focal loss  Semantic-visual alignment  Auto-encoder architecture  
A Novel Adaptive Parameter Search Elastic Net Method for Fluorescent Molecular Tomography 期刊论文
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021, 卷号: 40, 期号: 5, 页码: 1484-1498
作者:  Wang, Hanfan;  Bian, Chang;  Kong, Lingxin;  An, Yu;  Du, Yang;  Tian, Jie
Adobe PDF(8176Kb)  |  收藏  |  浏览/下载：448/74  |  提交时间：2021/06/15
Image reconstruction  Fluorescence  Probes  Mathematical model  Photonics  Molecular imaging  Biological tissues  Fluorescence molecular tomography  adaptive parameter search  elastic net  
Classification of Severe and Critical Covid-19 Using Deep Learning and Radiomics 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3585-3594
作者:  Li, Cong;  Dong, Di;  Li, Liang;  Gong, Wei;  Li, Xiaohu;  Bai, Yan;  Wang, Meiyun;  Hu, Zhenhua;  Zha, Yunfei;  Tian, Jie
Adobe PDF(2325Kb)  |  收藏  |  浏览/下载：424/65  |  提交时间：2021/03/02
COVID-19  radiomics  deep learning  computed tomography (CT)  
A Deep Learning Prognosis Model Help Alert for COVID-19 Patients at High-Risk of Death: A Multi-Center Study 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3576-3584
作者:  Meng, Lingwei;  Dong, Di;  Li, Liang;  Niu, Meng;  Bai, Yan;  Wang, Meiyun;  Qiu, Xiaoming;  Zha, Yunfei;  Tian, Jie
Adobe PDF(4120Kb)  |  收藏  |  浏览/下载：359/64  |  提交时间：2021/03/02
COVID-19  Computed tomography  Lung  Hospitals  Biomedical imaging  Training  Coronavirus disease 2019 (COVID-19)  prognosis  computed tomography  deep learning  artificial intelligence