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Machine learning model for predicting physical activity related bleeding risk in Chinese boys with haemophilia A 期刊论文
THROMBOSIS RESEARCH, 2023, 卷号: 232, 页码: 43-53
作者:  Ai, Di;  Cui, Chang;  Tang, Yongqiang;  Wang, Yan;  Zhang, Ningning;  Zhang, Chenyang;  Zhen, Yingzi;  Li, Gang;  Huang, Kun;  Liu, Guoqing;  Chen, Zhenping;  Zhang, Wensheng;  Wu, Runhui
收藏  |  浏览/下载：43/0  |  提交时间：2024/03/26
Haemophilia  Children  Machine learning  Bleeding predictive modelling  Physical activity  
Zero-Shot Predicate Prediction for Scene Graph Parsing 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 卷号: 25, 页码: 3140-3153
作者:  Li, Yiming;  Yang, Xiaoshan;  Huang, Xuhui;  Ma, Zhe;  Xu, Changsheng
收藏  |  浏览/下载：166/0  |  提交时间：2023/11/17
Deep learning  zero-shot  scene graph  
An intelligent workflow for sub-nanoscale 3D reconstruction of intact synapses from serial section electron tomography 期刊论文
BMC BIOLOGY, 2023, 卷号: 21, 期号: 1, 页码: 14
作者:  Chang, Sheng;  Li, Linlin;  Hong, Bei;  Liu, Jing;  Xu, Yuxuan;  Pang, Keliang;  Zhang, Lina;  Han, Hua;  Chen, Xi
收藏  |  浏览/下载：118/0  |  提交时间：2023/11/16
Serial section electron tomography  3D EM  Semi-auto locating  Auto-alignment  Missing-information restoration  Semi-auto segmentation  Workflow  Synapse  
Denoising of scanning electron microscope images for biological ultrastructure enhancement 期刊论文
JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 2022, 卷号: 20, 期号: 03, 页码: 21
作者:  Chang, Sheng;  Shen, Lijun;  Li, Linlin;  Chen, Xi;  Han, Hua
Adobe PDF(4726Kb)  |  收藏  |  浏览/下载：323/45  |  提交时间：2022/09/19
SEM  noise model  denoising  variance stabilization transformation  two-stage multi-loss  deep learning  
Domain-invariant Graph for Adaptive Semi-supervised Domain Adaptation 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2022, 卷号: 18, 期号: 3, 页码: 18
作者:  Li, Jinfeng;  Liu, Weifeng;  Zhou, Yicong;  Yu, Jun;  Tao, Dapeng;  Xu, Changsheng
收藏  |  浏览/下载：280/0  |  提交时间：2022/06/10
Domain adaptation  domain-invariant graph  the Nystrom method  few labeled source samples  
Adversarial Multimodal Network for Movie Story Question Answering 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 1744-1756
作者:  Yuan, Zhaoquan;  Sun, Siyuan;  Duan, Lixin;  Li, Changsheng;  Wu, Xiao;  Xu, Changsheng
收藏  |  浏览/下载：196/0  |  提交时间：2021/08/15
Knowledge discovery  Motion pictures  Visualization  Task analysis  Generators  Gallium nitride  Natural languages  Movie question answering  adversarial network  multimodal understanding  
Distribution Aligned Multimodal and Multi-Domain Image Stylization 期刊论文
ACM Transactions on Multimedia Computing, Communications, and Applications, 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Minxuan, Lin;  Fan, Tang;  Weiming, Dong;  Xiao, Li;  Changsheng, Xu;  Chongyang, Ma
Adobe PDF(83286Kb)  |  收藏  |  浏览/下载：241/45  |  提交时间：2021/07/07
image stylization  multi-domain  multimodal  
Intra-domain Consistency Enhancement for Unsupervised Person Re-identification 期刊论文
IEEE Transactions on Multimedia, 2021, 卷号: 0, 期号: 0, 页码: 0-0
作者:  Li, Yaoyu;  Yao, Hantao;  Xu, Changsheng
Adobe PDF(2167Kb)  |  收藏  |  浏览/下载：219/62  |  提交时间：2021/06/22
Person Re-identification  unsupervised domain adaptation  representation learning  
Part-based Structured Representation Learning for Person Re-identification 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 卷号: 16, 期号: 4, 页码: 22
作者:  Li, Yaoyu;  Yao, Hantao;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(19052Kb)  |  收藏  |  浏览/下载：322/46  |  提交时间：2021/03/08
Person re-identification  representation learning  graph convolutional network  
Density-Aware Multi-Task Learning for Crowd Counting 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 443-453
作者:  Jiang, Xiaoheng;  Zhang, Li;  Zhang, Tianzhu;  Lv, Pei;  Zhou, Bing;  Pang, Yanwei;  Xu, Mingliang;  Xu, Changsheng
收藏  |  浏览/下载：302/0  |  提交时间：2021/03/08
Task analysis  Semantics  Estimation  Feature extraction  Convolutional neural networks  Cameras  Head  Convolutional neural network  crowd counting  density-level classification  density map estimation  multi-task learning