1.1k citations · 5.5k across the 27 of their papers we have counts for
27 papers
A Novel Technique for Robust Training of Deep Networks With Multisource Weak Labeled Remote Sensing Data
Gianmarco Perantoni, Lorenzo Bruzzone
Deep learning has gained broad interest in remote sensing image scene classification thanks to the effectiveness of deep neural networks in extracting the semantics from complex da…
Incomplete Multimodal Learning for Remote Sensing Data Fusion
Yuxing Chen, Maofan Zhao, Lorenzo Bruzzone
The mechanism of connecting multimodal signals through self-attention operation is a key factor in the success of multimodal Transformer networks in remote sensing data fusion task…
Unsupervised CD in satellite image time series by contrastive learning and feature tracking
Yuxing Chen, Lorenzo Bruzzone
While unsupervised change detection using contrastive learning has been significantly improved the performance of literature techniques, at present, it only focuses on the bi-tempo…
Jupiter Science Enabled by ESA's Jupiter Icy Moons Explorer
Leigh N. Fletcher, Thibault Cavalié, Davide Grassi +47
ESA's Jupiter Icy Moons Explorer (JUICE) will provide a detailed investigation of the Jovian system in the 2030s, combining a suite of state-of-the-art instruments with an orbital…
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…
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…
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…
Remote Sensing Image Scene Classification with Deep Neural Networks in JPEG 2000 Compressed Domain
Akshara Preethy Byju, Gencer Sumbul, Begüm Demir +1
To reduce the storage requirements, remote sensing (RS) images are usually stored in compressed format. Existing scene classification approaches using deep neural networks (DNNs) r…
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,…
Lunar impact craters identification and age estimation with Chang'E data by deep and transfer learning
Chen Yang, Haishi Zhao, Lorenzo Bruzzone +7
Impact craters, as "lunar fossils", are the most dominant lunar surface features and occupy most of the Moon's surface. Their formation and evolution record the history of the Sola…
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…
Multisource and Multitemporal Data Fusion in Remote Sensing
Pedram Ghamisi, Behnood Rasti, Naoto Yokoya +9
The sharp and recent increase in the availability of data captured by different sensors combined with their considerably heterogeneous natures poses a serious challenge for the eff…
Tensor Alignment Based Domain Adaptation for Hyperspectral Image Classification
Yao Qin, Lorenzo Bruzzone, Biao Li
This paper presents a tensor alignment (TA) based domain adaptation method for hyperspectral image (HSI) classification. To be specific, HSIs in both domains are first segmented in…
A local fingerprint for hydrophobicity and hydrophilicity: from methane to peptides
S. Pérez-Conesa, Pablo M. Piaggi, Michele Parrinello
An important characteristic that determines the behavior of a solute in water is whether it is hydrophobic or hydrophilic. The traditional classification is based on chemical exper…
Fast and Robust Matching for Multimodal Remote Sensing Image Registration
Yuanxin Ye, Lorenzo Bruzzone, Jie Shan +2
While image registration has been studied in remote sensing community for decades, registering multimodal data [e.g., optical, LiDAR, SAR, and map] remains a challenging problem be…
Recent Developments from Attribute Profiles for Remote Sensing Image Classification
Minh-Tan Pham, Sébastien Lefèvre, Erchan Aptoula +1
Morphological attribute profiles (APs) are among the most effective methods to model the spatial and contextual information for the analysis of remote sensing images, especially fo…