SEN12MS – A CURATED DATASET OF GEOREFERENCED MULTI-SPECTRAL SENTINEL-1/2 IMAGERY FOR DEEP LEARNING AND DATA FUSION

136 citations as recorded by crossref.

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18. Multisensor Data Fusion for Cloud Removal in Global and All-Season Sentinel-2 Imagery P. Ebel et al. 10.1109/TGRS.2020.3024744
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20. Distilled Heterogeneous Feature Alignment Network for SAR Image Semantic Segmentation M. Gao et al. 10.1109/LGRS.2023.3293160
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23. FG-GAN: A Fine-Grained Generative Adversarial Network for Unsupervised SAR-to-Optical Image Translation X. Yang et al. 10.1109/TGRS.2022.3165371
24. Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion A. Meraner et al. 10.1016/j.isprsjprs.2020.05.013
25. Multi-Relation Attention Network for Image Patch Matching D. Quan et al. 10.1109/TIP.2021.3101414
26. TransFusion-CR: Two-Phase SAR-to-Optical Translation and Deep Feature Fusion for Cloud Removal R. Liu et al. 10.1109/TGRS.2024.3439854
27. Computer Vision and Pattern Recognition for the Analysis of 2D/3D Remote Sensing Data in Geoscience: A Survey M. Savelonas et al. 10.3390/rs14236017
28. S1S2-Water: A Global Dataset for Semantic Segmentation of Water Bodies From Sentinel- 1 and Sentinel-2 Satellite Images M. Wieland et al. 10.1109/JSTARS.2023.3333969
29. A Weakly Supervised Semantic Segmentation Framework for Medium-Resolution Forest Classification With Noisy Labels and GF-1 WFV Images X. Peng et al. 10.1109/TGRS.2024.3404953
30. A super-ensemble approach to map land cover types with high resolution over data-sparse African savanna landscapes L. Song et al. 10.1016/j.jag.2022.103152
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41. Reconstruction Bias U-Net for Road Extraction From Optical Remote Sensing Images Z. Chen et al. 10.1109/JSTARS.2021.3053603
42. SEN12MS-CR-TS: A Remote-Sensing Data Set for Multimodal Multitemporal Cloud Removal P. Ebel et al. 10.1109/TGRS.2022.3146246
43. Deep Species Distribution Modeling From Sentinel-2 Image Time-Series: A Global Scale Analysis on the Orchid Family J. Estopinan et al. 10.3389/fpls.2022.839327
44. Learning SAR-to-Optical Image Translation via Diffusion Models With Color Memory Z. Guo et al. 10.1109/JSTARS.2024.3439516
45. Beyond Supervised Learning in Remote Sensing: A Systematic Review of Deep Learning Approaches B. Hosseiny et al. 10.1109/JSTARS.2023.3316733
46. Learning a Joint Embedding of Multiple Satellite Sensors: A Case Study for Lake Ice Monitoring M. Tom et al. 10.1109/TGRS.2022.3211184
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51. Multimodal Supervised Contrastive Learning in Remote Sensing Downstream Tasks P. Berg et al. 10.1109/LGRS.2024.3385995
52. 2020 IEEE GRSS Data Fusion Contest: Global Land Cover Mapping With Weak Supervision [Technical Committees] N. Yokoya et al. 10.1109/MGRS.2020.2970124
53. A Globally Applicable Method for NDVI Estimation from Sentinel-1 SAR Backscatter Using a Deep Neural Network and the SEN12TP Dataset T. Roßberg & M. Schmitt 10.1007/s41064-023-00238-y
54. On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances, and Million-AID Y. Long et al. 10.1109/JSTARS.2021.3070368
55. CERMF-Net: A SAR-Optical Feature Fusion for Cloud Elimination From Sentinel-2 Imagery Using Residual Multiscale Dilated Network J. Anandakrishnan et al. 10.1109/JSTARS.2024.3411032
56. Review on Convolutional Neural Networks (CNN) in vegetation remote sensing T. Kattenborn et al. 10.1016/j.isprsjprs.2020.12.010
57. deepNIR: Datasets for Generating Synthetic NIR Images and Improved Fruit Detection System Using Deep Learning Techniques I. Sa et al. 10.3390/s22134721
58. AmazonCRIME: un conjunto de datos y punto de referencia de Inteligencia Artificial Geoespacial para la clasificación de áreas potenciales vinculadas a Crímenes Ambientales Transnacionales en la Selva Amazónica J. Pinto-Hidalgo & J. Silva-Centeno 10.4995/raet.2022.15710
59. Advancing horizons in remote sensing: a comprehensive survey of deep learning models and applications in image classification and beyond S. Paheding et al. 10.1007/s00521-024-10165-7
60. Contrastive Self-Supervised Learning for Globally Distributed Landslide Detection O. Ghorbanzadeh et al. 10.1109/ACCESS.2024.3449447
61. The Eyes of the Gods: A Survey of Unsupervised Domain Adaptation Methods Based on Remote Sensing Data M. Xu et al. 10.3390/rs14174380
62. Deep Image Prior Amplitude SAR Image Anonymization E. Cannas et al. 10.3390/rs15153750
63. NaSC-TG2: Natural Scene Classification With Tiangong-2 Remotely Sensed Imagery Z. Zhou et al. 10.1109/JSTARS.2021.3063096
64. Towards Synoptic Water Monitoring Systems: A Review of AI Methods for Automating Water Body Detection and Water Quality Monitoring Using Remote Sensing L. Yang et al. 10.3390/s22062416
65. Bare Soil Extraction from Sentinel-2 Images with Weakly Supervised and Spectral Index 燚. 赵 10.12677/JSTA.2024.121005
66. High-Resolution Land-Cover Mapping Based on a Cross-Resolution Deep Learning Framework and Available Low-Resolution Labels X. Qi et al. 10.1109/JSTARS.2023.3342994
67. A Workflow for Collecting and Preprocessing Sentinel-1 Images for Time Series Prediction Suitable for Deep Learning Algorithms W. Moskolaï et al. 10.3390/geomatics2040024
68. Large-Scale Land Cover Mapping Framework Based on Prior Product Label Generation: A Case Study of Cambodia H. Zhu et al. 10.3390/rs16132443
69. Meta-FSEO: A Meta-Learning Fast Adaptation with Self-Supervised Embedding Optimization for Few-Shot Remote Sensing Scene Classification Y. Li et al. 10.3390/rs13142776
70. Two-Way Generation of High-Resolution EO and SAR Images via Dual Distortion-Adaptive GANs Y. Qing et al. 10.3390/rs15071878
71. A framework for large-scale mapping of human settlement extent from Sentinel-2 images via fully convolutional neural networks C. Qiu et al. 10.1016/j.isprsjprs.2020.01.028
72. Object Detection and Image Segmentation with Deep Learning on Earth Observation Data: A Review—Part II: Applications T. Hoeser et al. 10.3390/rs12183053
73. WTS: A Weakly towards Strongly Supervised Learning Framework for Remote Sensing Land Cover Classification Using Segmentation Models W. Zhang et al. 10.3390/rs13030394
74. Feature Interaction Learning Network for Cross-Spectral Image Patch Matching C. Yu et al. 10.1109/TIP.2023.3313488
75. Combining Deep Learning and Multi-Source GIS Methods to Analyze Urban and Greening Changes M. Francini et al. 10.3390/s23083805
76. Cloud-Guided Fusion With SAR-to-Optical Translation for Thick Cloud Removal X. Xiang et al. 10.1109/TGRS.2024.3431556
77. GLUENet: An Efficient Network for Remote Sensing Image Dehazing with Gated Linear Units and Efficient Channel Attention J. Fang et al. 10.3390/rs16081450
78. MapInWild: A remote sensing dataset to address the question of what makes nature wild [Software and Data Sets] B. Ekim et al. 10.1109/MGRS.2022.3226525
79. Water body classification from high-resolution optical remote sensing imagery: Achievements and perspectives Y. Li et al. 10.1016/j.isprsjprs.2022.03.013
80. Flood Detection with SAR: A Review of Techniques and Datasets D. Amitrano et al. 10.3390/rs16040656
81. DeepForest: Novel Deep Learning Models for Land Use and Land Cover Classification Using Multi-Temporal and -Modal Sentinel Data of the Amazon Basin E. Cherif et al. 10.3390/rs14195000
82. TreeSatAI Benchmark Archive: a multi-sensor, multi-label dataset for tree species classification in remote sensing S. Ahlswede et al. 10.5194/essd-15-681-2023
83. Joint Network Combining Dual-Attention Fusion Modality and Two Specific Modalities for Land Cover Classification Using Optical and SAR Images X. Liu et al. 10.1109/JSTARS.2023.3347571
84. ISSLIDE: A New InSAR Dataset for Slow SLIding Area DEtection With Machine Learning A. Bralet et al. 10.1109/LGRS.2024.3365299
85. A Novel Coarse-to-Fine Deep Learning Registration Framework for Multimodal Remote Sensing Images D. Quan et al. 10.1109/TGRS.2023.3306042
86. cuFSDAF: An Enhanced Flexible Spatiotemporal Data Fusion Algorithm Parallelized Using Graphics Processing Units H. Gao et al. 10.1109/TGRS.2021.3080384
87. Rearranging Pixels is a Powerful Black-Box Attack for RGB and Infrared Deep Learning Models J. Pomponi et al. 10.1109/ACCESS.2023.3241360
88. Cloud removal for optical remote sensing imagery using the SPA-CycleGAN network R. Jing et al. 10.1117/1.JRS.16.034520
89. A Unified Deep Learning Network for Remote Sensing Image Registration and Change Detection R. Zhou et al. 10.1109/TGRS.2023.3344751
90. Cloud Removal Based on SAR-Optical Remote Sensing Data Fusion via a Two-Flow Network R. Mao et al. 10.1109/JSTARS.2022.3203508
91. AgriSen-COG, a Multicountry, Multitemporal Large-Scale Sentinel-2 Benchmark Dataset for Crop Mapping Using Deep Learning T. Selea 10.3390/rs15122980
92. Exploring Archetypes of Tropical Fire-Related Forest Disturbances Based on Dense Optical and Radar Satellite Data and Active Fire Alerts J. Balling et al. 10.3390/f12040456
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95. Domain Adaptation for Mapping LCZs in Sub-Saharan Africa With Remote Sensing: A Comprehensive Approach to Health Data Analysis B. Rousse et al. 10.1109/JSTARS.2024.3421284
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100. SOSSF: Landsat-8 Image Synthesis on the Blending of Sentinel-1 and MODIS Data Y. Xia et al. 10.1109/TGRS.2024.3352662
101. Hybrid cGAN: Coupling Global and Local Features for SAR-to-Optical Image Translation Z. Wang et al. 10.1109/TGRS.2022.3212208
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108. Reproducibility and Replicability in SAR Remote Sensing T. Balz & F. Rocca 10.1109/JSTARS.2020.3005912
109. Time-series surface water reconstruction method (TSWR) based on spatial distance relationship of multi-stage water boundaries M. Li et al. 10.1080/17538947.2022.2159553
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128. Interpretable Deep Learning Framework for Land Use and Land Cover Classification in Remote Sensing Using SHAP A. Temenos et al. 10.1109/LGRS.2023.3251652
129. Inter-satellite variability of grassland curing maps produced by different satellite sensors – Victoria, Australia S. Li 10.1080/17538947.2021.1900938
130. Time-Aware Dual LSTM Neural Network with Similarity Graph Learning for Remote Sensing Service Recommendation J. Zhang et al. 10.3390/s24041185
131. Remote Sensing Mapping of Build-Up Land with Noisy Label via Fault-Tolerant Learning G. Xu et al. 10.3390/rs14092263
132. Global perspectives on sand dune patterns: Scale-adaptable classification using Landsat imagery and deep learning strategies Z. Zheng et al. 10.1016/j.isprsjprs.2024.10.002
133. A Flexible Multi-Temporal and Multi-Modal Framework for Sentinel-1 and Sentinel-2 Analysis Ready Data P. Upadhyay et al. 10.3390/rs14051120
134. Multi-Label Remote Sensing Image Land Cover Classification Based on a Multi-Dimensional Attention Mechanism H. You et al. 10.3390/rs15204979
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