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Bi-Temporal Semantic Reasoning for the Semantic Change Detection in HR Remote Sensing Images
Lei Ding, Haitao Guo, Sicong Liu +3
Semantic change detection (SCD) extends the multi-class change detection (MCD) task to provide not only the change locations but also the detailed land-cover/land-use (LCLU) catego…
Looking Outside the Window: Wide-Context Transformer for the Semantic Segmentation of High-Resolution Remote Sensing Images
Lei Ding, Dong Lin, Shaofu Lin +5
Long-range contextual information is crucial for the semantic segmentation of High-Resolution (HR) Remote Sensing Images (RSIs). However, image cropping operations, commonly used f…
Self-supervised Remote Sensing Images Change Detection at Pixel-level
Yuxing Chen, Lorenzo Bruzzone
Deep learning techniques have achieved great success in remote sensing image change detection. Most of them are supervised techniques, which usually require large amounts of traini…
Recent Advances in Domain Adaptation for the Classification of Remote Sensing Data
Devis Tuia, Claudio Persello, Lorenzo Bruzzone
The success of supervised classification of remotely sensed images acquired over large geographical areas or at short time intervals strongly depends on the representativity of the…
Robust Registration of Multimodal Remote Sensing Images Based on Structural Similarity
Yuanxin Ye, Jie Shan, Lorenzo Bruzzone +1
Automatic registration of multimodal remote sensing data (e.g., optical, LiDAR, SAR) is a challenging task due to the significant non-linear radiometric differences between these d…
Deep Reinforcement Learning for Band Selection in Hyperspectral Image Classification
Lichao Mou, Sudipan Saha, Yuansheng Hua +3
Band selection refers to the process of choosing the most relevant bands in a hyperspectral image. By selecting a limited number of optimal bands, we aim at speeding up model train…
Self-supervised Change Detection in Multi-view Remote Sensing Images
Yuxing Chen, Lorenzo Bruzzone
The vast amount of unlabeled multi-temporal and multi-sensor remote sensing data acquired by the many Earth Observation satellites present a challenge for change detection. Recentl…
Self-supervised SAR-optical Data Fusion and Land-cover Mapping using Sentinel-1/-2 Images
Yuxing Chen, Lorenzo Bruzzone
The effective combination of the complementary information provided by the huge amount of unlabeled multi-sensor data (e.g., Synthetic Aperture Radar (SAR) and optical images) is a…
Adversarial Shape Learning for Building Extraction in VHR Remote Sensing Images
Lei Ding, Hao Tang, Yahui Liu +3
Building extraction in VHR RSIs remains a challenging task due to occlusion and boundary ambiguity problems. Although conventional convolutional neural networks (CNNs) based method…