414 citations · 1.2k across the 9 of their papers we have counts for
9 papers
Joint Spatio-Temporal Modeling for the Semantic Change Detection in Remote Sensing Images
Lei Ding, Jing Zhang, Kai Zhang +3
Semantic Change Detection (SCD) refers to the task of simultaneously extracting the changed areas and the semantic categories (before and after the changes) in Remote Sensing Image…
Deep Unsupervised Key Frame Extraction for Efficient Video Classification
Hao Tang, Lei Ding, Songsong Wu +3
Video processing and analysis have become an urgent task since a huge amount of videos (e.g., Youtube, Hulu) are uploaded online every day. The extraction of representative key fra…
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…
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…
MP-ResNet: Multi-path Residual Network for the Semantic segmentation of High-Resolution PolSAR Images
Lei Ding, Kai Zheng, Dong Lin +4
There are limited studies on the semantic segmentation of high-resolution Polarimetric Synthetic Aperture Radar (PolSAR) images due to the scarcity of training data and the inferen…
Active Deep Densely Connected Convolutional Network for Hyperspectral Image Classification
Bing Liu, Anzhu Yu, Pengqiang Zhang +4
Deep learning based methods have seen a massive rise in popularity for hyperspectral image classification over the past few years. However, the success of deep learning is attribut…
DiResNet: Direction-aware Residual Network for Road Extraction in VHR Remote Sensing Images
Lei Ding, Lorenzo Bruzzone
The binary segmentation of roads in very high resolution (VHR) remote sensing images (RSIs) has always been a challenging task due to factors such as occlusions (caused by shadows,…
Improving Semantic Segmentation of Aerial Images Using Patch-based Attention
Lei Ding, Hao Tang, Lorenzo Bruzzone
The trade-off between feature representation power and spatial localization accuracy is crucial for the dense classification/semantic segmentation of aerial images. High-level feat…