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XANet: An Efficient Remote Sensing Image Segmentation Model Using Element-Wise Attention Enhancement and Multi-Scale Attention Fusion 期刊论文
REMOTE SENSING, 2023, 卷号: 15, 期号: 1, 页码: 25
作者:  Liang, Chenbin;  Xiao, Baihua;  Cheng, Bo;  Dong, Yunyun
Adobe PDF(63859Kb)  |  收藏  |  浏览/下载：403/25  |  提交时间：2023/02/22
semantic segmentation  attention mechanism  cross-attention  feature fusion  
High-Resolution Boundary Refined Convolutional Neural Network for Automatic Agricultural Greenhouses Extraction from GaoFen-2 Satellite Imageries 期刊论文
REMOTE SENSING, 2021, 卷号: 13, 期号: 21, 页码: 25
作者:  Zhang, Xiaoping;  Cheng, Bo;  Chen, Jinfen;  Liang, Chenbin
收藏  |  浏览/下载：187/0  |  提交时间：2021/12/28
Agricultural Greenhouses  DCNN  Semantic Segmentation  high resolution  context integration  boundary refined  GaoFen-2  
Semi-/Weakly-Supervised Semantic Segmentation Method and Its Application for Coastal Aquaculture Areas Based on Multi-Source Remote Sensing Images-Taking the Fujian Coastal Area (Mainly Sanduo) as an Example 期刊论文
REMOTE SENSING, 2021, 卷号: 13, 期号: 6, 页码: 21
作者:  Liang, Chenbin;  Cheng, Bo;  Xiao, Baihua;  He, Chenlinqiu;  Liu, Xunan;  Jia, Ning;  Chen, Jinfen
Adobe PDF(66625Kb)  |  收藏  |  浏览/下载：259/17  |  提交时间：2021/08/15
coastal aquaculture areas  semantic segmentation  semi-  weakly-supervised learning  GAN  conditional adversarial learning  
Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap 期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 22, 页码: 15
作者:  Zhao, Yong;  Cheng, Yuqi;  Zhang, Xishan;  Xu, Shibiao;  Bu, Shuhui;  Jiang, Hongkai;  Han, Pengcheng;  Li, Ke;  Wan, Gang
收藏  |  浏览/下载：256/0  |  提交时间：2021/01/06
aerial images  DOM  low overlap  mosaicing  georeferenced  orthophoto  
Hyperspectral Imagery Classification Based on Semi-Supervised Broad Learning System 期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 5, 页码: 13
作者:  Kong, Yi;  Wang, Xuesong;  Cheng, Yuhu;  Chen, C. L. Philip
收藏  |  浏览/下载：145/0  |  提交时间：2019/12/16
hyperspectral imagery  classification  broad learning  semi-supervised  class-probability structure