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20172025
most citedRecent Advances in Domain Adaptation for the Classification of Remote Sensing Data

644 citations · 1.2k across the 5 of their papers we have counts for

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9 papers · 1 filter

cs.CV202514 cited

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…

cs.CV20234 cited

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…

cs.CV2023

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…

cs.CV2021644 cited

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…

cs.CV2021482 cited

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…

cs.CV2020

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…