A Dual-Branch Deep Learning Architecture for Multisensor and Multitemporal Remote Sensing Semantic Segmentation-Reference-Cited by-同舟云学术

A Dual-Branch Deep Learning Architecture for Multisensor and Multitemporal Remote Sensing Semantic Segmentation

Published:2023 Issue: Volume:16 Page:2147-2162
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Bergamasco Luca¹^ORCID,Bovolo Francesca¹^ORCID,Bruzzone Lorenzo²^ORCID

Affiliation:

1. Center for Digital Society, Fondazione Bruno Kessler, Trento, Italy

2. Department of Information Engineering and Computer Science, University of Trento, Trento, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9973430/10041791.pdf?arnumber=10041791

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1. Detecting Large-Scale Urban Land Cover Changes from Very High Resolution Remote Sensing Images Using CNN-Based Classification

2. U-Net: Convolutional networks for biomedical image segmentation;ronneberger;Proc Int Conf Med Image Comput Comput -Assist Interv,0

3. Recurrent Multiresolution Convolutional Networks for VHR Image Classification

4. Semantic segmentation of crop type in Africa: A novel dataset and analysis of deep learning methods;rustowicz;Proc IEEE/CVF Conf Comput Vis Pattern Recognit Workshops,0

5. Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas

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