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One-Class Remote Sensing Classification From Positive and Unlabeled Background Data 期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 卷号: 14, 页码: 730-746
作者:  Li, Wenkai;  Guo, Qinghua;  Elkan, Charles
Adobe PDF(11598Kb)  |  收藏  |  浏览/下载：73/0  |  提交时间：2023/02/24
Training  Remote sensing  Classification algorithms  Mathematical model  Support vector machines  Data models  Prediction algorithms  Case-control sampling  labeled and unlabeled data  one-class classification  positive and background learning with constraints (PBLC)  remote sensing  
A Framework for Land Use Scenes Classification Based on Landscape Photos 期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 卷号: 13, 页码: 6124-6141
作者:  Xu, Shiwu;  Zhang, Shihui;  Zeng, Jue;  Li, Tingyu;  Guo, Qinghua;  Jin, Shichao
Adobe PDF(6559Kb)  |  收藏  |  浏览/下载：90/0  |  提交时间：2022/03/01
Semantics  Remote sensing  Image analysis  Image segmentation  Object recognition  Machine learning  Forestry  Deep convolutional neural networks (DCNNs)  landscape photos  land survey  land use scene classification  
A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments 期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 卷号: 13, 页码: 3958-3974
作者:  Jin, Shichao;  Sun, Yanjun;  Zhao, Xiaoqian;  Hu, Tianyu;  Guo, Qinghua
Adobe PDF(7633Kb)  |  收藏  |  浏览/下载：85/0  |  提交时间：2022/03/01
Digital terrain model (DTM)  deep learning  fully convolutional neural network (FCN)  ground filtering  light detection and ranging (LiDAR)  
An Ensemble of Classifiers Based on Positive and Unlabeled Data in One-Class Remote Sensing Classification 期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 卷号: 11, 期号: 2, 页码: 572-584
作者:  Liu, Ran;  Li, Wenkai;  Liu, Xiaoping;  Lu, Xingcheng;  Li, Tianhong;  Guo, Qinghua
Adobe PDF(9506Kb)  |  收藏  |  浏览/下载：77/0  |  提交时间：2022/02/25
Classifier ensemble  one-class classification  positive and unlabeled learning (PUL)  weighted average  weighted vote