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Meta Graph Transformer: A Novel Framework for Spatial-Temporal Traffic Prediction 期刊论文
NEUROCOMPUTING, 2022, 卷号: 491, 页码: 544-563
作者:  Ye, Xue;  Fang, Shen;  Sun, Fang;  Zhang, Chunxia;  Xiang, Shiming
Adobe PDF(3491Kb)  |  收藏  |  浏览/下载：209/24  |  提交时间：2022/09/19
Traffic prediction  Spatial-temporal modeling  Meta-learning  Attention mechanism  Deep learning  
Color‐Guided Depth Map Super‐Resolution Using a Dual‐Branch Multi‐Scale Residual Network with Channel Interaction 期刊论文
Sensors, 2020, 卷号: 20, 期号: 6, 页码: 1560
作者:  陈睿进;  高伟
浏览  |  Adobe PDF(2336Kb)  |  收藏  |  浏览/下载：253/62  |  提交时间：2020/04/30
Depth Map  Super‐resolution  Guidance  Residual Network  Channel Interaction  
Instance segmentation of apple flowers using the improved mask R-CNN model 期刊论文
biosystems engineering, 2020, 期号: 193, 页码: 264-278
作者:  Tian YN(田雨农)
Adobe PDF(4718Kb)  |  收藏  |  浏览/下载：150/37  |  提交时间：2022/01/06
Apple flower images acquisition  Apple flower images acquisition  Deep learning  MASU R-CNN  Instance segmentation  
BRANT: A Versatile and Extendable Resting-State fMRI Toolkit 期刊论文
FRONTIERS IN NEUROINFORMATICS, 2018, 卷号: 12, 期号: -, 页码: 52
作者:  Xu, Kaibin;  Liu, Yong;  Zhan, Yafeng;  Ren, Jiaji;  Jiang, Tianzi
浏览  |  Adobe PDF(4680Kb)  |  收藏  |  浏览/下载：320/39  |  提交时间：2018/10/10
BRANT  resting-state fMRI  code-generated GUI  preprocessing  visualization  
Automatic extraction and identification of narrow butt joint based on ANFIS before GMAW 期刊论文
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2018, 卷号: 100, 期号: 1-4, 页码: 609-622
作者:  Lei,yang;  En,li;  Junfeng,fan;  Teng,long;  Zize,liang
浏览  |  Adobe PDF(2666Kb)  |  收藏  |  浏览/下载：241/67  |  提交时间：2019/04/24
Narrow Butt Joint, Weak Contrast, Extraction, Identification, Anfis  
Effective automated pipeline for 3D reconstruction of synapses based on deep learning 期刊论文
BMC Bioinformatics, 2018, 卷号: 19, 期号: 1, 页码: 263
作者:  Xiao, Chi;  Li, Weifu;  Deng, Hao;  Chen, Xi;  Yang, Yang;  Xie, QiWei;  Han, Hua
浏览  |  Adobe PDF(7961Kb)  |  收藏  |  浏览/下载：304/96  |  提交时间：2019/05/06
Electron Microscope, Synapse Detection, Deep Learning, Synapse Segmentation, 3d Reconstruction Of Synapses