Automatic Extraction of Water and Shadow from SAR Images Based on a Multi-Resolution Dense Encoder and Decoder Network
出版年份 2019 全文链接
标题
Automatic Extraction of Water and Shadow from SAR Images Based on a Multi-Resolution Dense Encoder and Decoder Network
作者
关键词
-
出版物
SENSORS
Volume 19, Issue 16, Pages 3576
出版商
MDPI AG
发表日期
2019-08-19
DOI
10.3390/s19163576
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- A New Deep Learning Algorithm for SAR Scene Classification Based on Spatial Statistical Modeling and Features Re-Calibration
- (2019) Lifu Chen et al. SENSORS
- Road Network Extraction From Low-Contrast SAR Images
- (2019) Tao Zeng et al. IEEE Geoscience and Remote Sensing Letters
- DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
- (2018) Liang-Chieh Chen et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Integrating Aerial and Street View Images for Urban Land Use Classification
- (2018) Rui Cao et al. Remote Sensing
- Deep Convolutional Highway Unit Network for SAR Target Classification With Limited Labeled Training Data
- (2017) Zhao Lin et al. IEEE Geoscience and Remote Sensing Letters
- Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data
- (2017) Nataliia Kussul et al. IEEE Geoscience and Remote Sensing Letters
- Deep Supervised and Contractive Neural Network for SAR Image Classification
- (2017) Jie Geng et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Fusion of SAR, Optical Imagery and Airborne LiDAR for Surface Water Detection
- (2017) Katherine Irwin et al. Remote Sensing
- Transfer Learning with Deep Convolutional Neural Network for SAR Target Classification with Limited Labeled Data
- (2017) Zhongling Huang et al. Remote Sensing
- SAR Image Classification via Hierarchical Sparse Representation and Multisize Patch Features
- (2016) Biao Hou et al. IEEE Geoscience and Remote Sensing Letters
- Target Classification Using the Deep Convolutional Networks for SAR Images
- (2016) Sizhe Chen et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Water-Body types identification in urban areas from radarsat-2 fully polarimetric SAR data
- (2016) Lei Xie et al. International Journal of Applied Earth Observation and Geoinformation
- Building detection and building parameter retrieval in InSAR phase images
- (2016) Clémence Dubois et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- High-Resolution SAR Image Classification via Deep Convolutional Autoencoders
- (2015) Jie Geng et al. IEEE Geoscience and Remote Sensing Letters
- Deep Learning Based Feature Selection for Remote Sensing Scene Classification
- (2015) Qin Zou et al. IEEE Geoscience and Remote Sensing Letters
- Flooding Water Depth Estimation With High-Resolution SAR
- (2015) Pasquale Iervolino et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Comparing Near-Coincident C- and X-Band SAR Acquisitions of Marine Oil Spills
- (2015) Stine Skrunes et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Comparing four operational SAR-based water and flood detection approaches
- (2015) Sandro Martinis et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Water Area Extraction Using RADARSAT SAR Imagery Combined with Landsat Imagery and Terrain Information
- (2015) Seunghwan Hong et al. SENSORS
- Deep Learning-Based Classification of Hyperspectral Data
- (2014) Yushi Chen et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Fast threshold selection algorithm for segmentation of synthetic aperture radar images
- (2012) J. Jennifer Ranjani et al. IET Radar Sonar and Navigation
- Integration of InSAR Time-Series Analysis and Water-Vapor Correction for Mapping Postseismic Motion After the 2003 Bam (Iran) Earthquake
- (2009) Zhenhong Li et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
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