机构

• 地理科学与资源研究所 [9]

采集方式

• OAI收割 [9]

内容类型

• 期刊论文 [9]

发表日期

• 2023 [2]
• 2022 [1]
• 2021 [6]

学科主题

筛选

浏览/检索结果: 共9条，第1-9条 帮助 限定条件 专题：地理科学与资源研究所    第一署名单位    第一作者单位    通讯作者单位     条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 CNN-TransNet: A Hybrid CNN-Transformer Network With Differential Feature Enhancement for Cloud Detection 期刊论文  OAI收割 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 卷号: 20, 页码: 5 作者:  Ma, Nan;  Sun, Lin;  He, Yawen;  Zhou, Chenghu;  Dong, Chuanxiang   |  收藏  |  浏览/下载：5/0  |  提交时间：2023/10/09 Cloud detection  convolutional neural network (CNN)  differential feature  dual branch  transformer   Coastal Zone Extraction Algorithm Based on Multilayer Depth Features for Hyperspectral Images 期刊论文  OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 卷号: 61, 页码: 15 作者:  Qiu, Shi;  Ye, Huping;  Liao, Xiaohan   |  收藏  |  浏览/下载：6/0  |  提交时间：2023/11/29 Feature extraction  Hyperspectral imaging  Sea measurements  Convolutional neural networks  Three-dimensional displays  Remote sensing  Water quality  3-D convolutional neural network (CNN)  depth characteristic  hyperspectrum  multilevel  remote sensing  squeeze and excitation network (SENet)   A CNN-LSTM Model for Soil Organic Carbon Content Prediction with Long Time Series of MODIS-Based Phenological Variables 期刊论文  OAI收割 REMOTE SENSING, 2022, 卷号: 14, 期号: 18, 页码: 18 作者:  Zhang, Lei;  Cai, Yanyan;  Huang, Haili;  Li, Anqi;  Yang, Lin   |  收藏  |  浏览/下载：28/0  |  提交时间：2022/11/09 soil organic carbon  land surface phenology  deep learning  predictive mapping  convolutional neural network (CNN)  long short-term memory (LSTM)   An Improved Deep Learning Approach for Retrieving Outfalls Into Rivers From UAS Imagery 期刊论文  OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 页码: 14 作者:  Huang, Yaohuan;  Wu, Chengbin;  Yang, Haijun;  Zhu, Haitao;  Chen, Mingxing   |  收藏  |  浏览/下载：14/0  |  提交时间：2022/09/21 Rivers  Visualization  Remote sensing  Manuals  Inspection  Water resources  Task analysis  Deep learning  digital surface model (DSM)  faster region convolutional neural network (R-CNN)  outfalls into river  unmanned aircraft systems (UAS) imagery   An Improved Deep Learning Approach for Retrieving Outfalls Into Rivers From UAS Imagery 期刊论文  OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 页码: 14 作者:  Huang, Yaohuan;  Wu, Chengbin;  Yang, Haijun;  Zhu, Haitao;  Chen, Mingxing   |  收藏  |  浏览/下载：20/0  |  提交时间：2022/09/21 Rivers  Visualization  Remote sensing  Manuals  Inspection  Water resources  Task analysis  Deep learning  digital surface model (DSM)  faster region convolutional neural network (R-CNN)  outfalls into river  unmanned aircraft systems (UAS) imagery   An unsupervised learning method with convolutional auto-encoder for vessel trajectory similarity computation 期刊论文  OAI收割 OCEAN ENGINEERING, 2021, 卷号: 225, 页码: 16 作者:  Liang, Maohan;  Liu, Ryan Wen;  Li, Shichen;  Xiao, Zhe;  Liu, Xin   |  收藏  |  浏览/下载：9/0  |  提交时间：2021/06/10 Automatic identification system (AIS)  Trajectory similarity  Trajectory clustering  Convolutional neural network (CNN)  Convolutional auto-encoder (CAE)   An unsupervised learning method with convolutional auto-encoder for vessel trajectory similarity computation 期刊论文  OAI收割 OCEAN ENGINEERING, 2021, 卷号: 225, 页码: 16 作者:  Liang, Maohan;  Liu, Ryan Wen;  Li, Shichen;  Xiao, Zhe;  Liu, Xin   |  收藏  |  浏览/下载：9/0  |  提交时间：2021/06/10 Automatic identification system (AIS)  Trajectory similarity  Trajectory clustering  Convolutional neural network (CNN)  Convolutional auto-encoder (CAE)   Hyperspectral Image Classification Using a Hybrid 3D-2D Convolutional Neural Networks 期刊论文  OAI收割 IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 卷号: 14, 页码: 7570-7588 作者:  Ghaderizadeh, Saeed;  Abbasi-Moghadam, Dariush;  Sharifi, Alireza;  Zhao, Na;  Tariq, Aqil   |  收藏  |  浏览/下载：22/0  |  提交时间：2021/11/05 Feature extraction  Three-dimensional displays  Convolution  Solid modeling  Hyperspectral imaging  Kernel  Convolutional neural networks  Convolutional neural network (CNN)  deep learning  hyperspectral image (HSI) classification  spectral-spatial features   Hyperspectral Image Classification Using a Hybrid 3D-2D Convolutional Neural Networks 期刊论文  OAI收割 IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 卷号: 14, 页码: 7570-7588 作者:  Ghaderizadeh, Saeed;  Abbasi-Moghadam, Dariush;  Sharifi, Alireza;  Zhao, Na;  Tariq, Aqil   |  收藏  |  浏览/下载：15/0  |  提交时间：2021/11/05 Feature extraction  Three-dimensional displays  Convolution  Solid modeling  Hyperspectral imaging  Kernel  Convolutional neural networks  Convolutional neural network (CNN)  deep learning  hyperspectral image (HSI) classification  spectral-spatial features