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Siamese Network Using Adaptive Background Superposition Initialization for Real-Time Object Tracking 期刊论文
Ieee Access, 2019, 卷号: 7, 页码: 119454-119464
作者:  J.N.Zhu;  T.Chen;  J.T.Cao
浏览  |  Adobe PDF(2165Kb)  |  收藏  |  浏览/下载：205/59  |  提交时间：2020/08/24
Adaptive background superposition initialization,channel attention,module,object tracking,Siamese network,Computer Science,Engineering,Telecommunications  
Object-independent image-based wavefront sensing approach using phase diversity images and deep learning 期刊论文
Optics Express, 2019, 卷号: 27, 期号: 18, 页码: 26102-26119
作者:  Q.Xin;  G.H.Ju;  C.Y.Zhang;  S.Y.Xu
浏览  |  Adobe PDF(2894Kb)  |  收藏  |  浏览/下载：177/58  |  提交时间：2020/08/24
retrieval,algorithm,optics  
Underwater Object Recognition Based on Deep Encoding-Decoding Network 期刊论文
Journal of Ocean University of China, 2019, 卷号: 18, 期号: 2, 页码: 376-382
作者:  X.H.Wang;  J.H.Ouyang;  D.Y.Li;  G.Zhang
浏览  |  Adobe PDF(464Kb)  |  收藏  |  浏览/下载：187/48  |  提交时间：2020/08/24
deep learning,transfer learning,encoding-decoding,underwater object,object recognition,Oceanography  
Background Subtraction With Real-Time Semantic Segmentation 期刊论文
Ieee Access, 2019, 卷号: 7, 页码: 153869-153884
作者:  D.D.Zeng;  X.Chen;  M.Zhu;  M.Goesele;  A.Kuijper
浏览  |  Adobe PDF(6097Kb)  |  收藏  |  浏览/下载：162/46  |  提交时间：2020/08/24
Background subtraction,foreground object detection,semantic,segmentation,video surveillance,density-estimation,Computer Science,Engineering,Telecommunications  
Combining background subtraction algorithms with convolutional neural network 期刊论文
Journal of Electronic Imaging, 2019, 卷号: 28, 期号: 1, 页码: 6
作者:  D.D.Zeng;  M.Zhu;  A.Kuijper
浏览  |  Adobe PDF(1748Kb)  |  收藏  |  浏览/下载：168/49  |  提交时间：2020/08/24
foreground object detection,convolutional neural network,CDnet 2014,dataset,video surveillance,object detection,Engineering,Optics,Imaging Science & Photographic Technology  
MCF3D: Multi-Stage Complementary Fusion for Multi-sensor 3D Object Detection 期刊论文
Ieee Access, 2019, 卷号: 7, 页码: 90801-90814
作者:  J.R.Wang;  M.Zhu;  D.Y.Sun;  B.Wang;  W.Gao;  H.Wei
浏览  |  Adobe PDF(6364Kb)  |  收藏  |  浏览/下载：151/27  |  提交时间：2020/08/24
3D object detection,multi-sensor fusion,attention mechanism,autonomous driving,cloud,Computer Science,Engineering,Telecommunications  
Research on Scene Classification Method of High-Resolution Remote Sensing Images Based on RFPNet 期刊论文
Applied Sciences-Basel, 2019, 卷号: 9, 期号: 10, 页码: 26
作者:  X.Zhang;  Y.C.Wang;  N.Zhang;  D.D.Xu;  B.Chen
浏览  |  Adobe PDF(11958Kb)  |  收藏  |  浏览/下载：183/34  |  提交时间：2020/08/24
convolutional neural network,ResNet,semantic information,remote,sensing images,scene classification,TensorFlow,satellite images,deep,representation,network,features,scale,Chemistry,Engineering,Materials Science,Physics  
Scene classification of high-resolution remote sensing images based on IMFNet 期刊论文
Journal of Applied Remote Sensing, 2019, 卷号: 13, 期号: 4, 页码: 21
作者:  X.Zhang;  Y.C.Wang;  N.Zhang;  D.D.Xu;  B.Chen;  G.L.Ben;  X.Wang
浏览  |  Adobe PDF(2648Kb)  |  收藏  |  浏览/下载：180/61  |  提交时间：2020/08/24
image processing,remote sensing,artificial intelligence,pattern,recognition,scene classification,convolutional neural-networks,deep,Environmental Sciences & Ecology,Remote Sensing,Imaging Science &,Photographic Technology  
Super-resolution imaging for infrared microscanning optical system 期刊论文
Optics Express, 2019, 卷号: 27, 期号: 5, 页码: 7719-7737
作者:  X.F.Zhang;  W.Huang;  M.F.Xu;  S.Q.Jia;  X.R.Xu;  F.B.Li;  Y.D.Zheng
浏览  |  Adobe PDF(5396Kb)  |  收藏  |  浏览/下载：140/55  |  提交时间：2020/08/24
Optical systems,Frequency domain analysis,Image denoising,Image reconstruction,Optical resolving power,Pixels,Scanning,Set theory,Textures,Thermography (imaging)  
Estimating Maize Above-Ground Biomass Using 3D Point Clouds of Multi-Source Unmanned Aerial Vehicle Data at Multi-Spatial Scales 期刊论文
Remote Sensing, 2019, 卷号: 11, 期号: 22, 页码: 22
作者:  W.X.Zhu;  Z.G.Sun;  J.B.Peng;  Y.H.Huang;  J.Li;  J.Q.Zhang
浏览  |  Adobe PDF(9111Kb)  |  收藏  |  浏览/下载：195/87  |  提交时间：2020/08/24
unmanned aerial vehicle,above-ground biomass,LiDAR,crop height,machine learning,canopy height,multispectral data,SfM point clouds,leaf-area index,crop surface models,winter-wheat,