Li Shen
Orcid: 0000-0003-4638-3329Affiliations:
- Southwest Jiaotong University, Faculty of Geosciences and Environmental Engineering, Chengdu, China
- Beijing Normal University, College of Resources Science and Technology, China (PhD 2013)
According to our database1,
Li Shen
authored at least 23 papers
between 2012 and 2024.
Collaborative distances:
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Bibliography
2024
A full-attention network with an open dataset for large-scale building semantic segmentation along long-span high-speed rail lines.
Int. J. Digit. Earth, December, 2024
A Weakly Supervised Bitemporal Scene Change Detection Approach for Pixel-Level Building Damage Assessment Using Pre- and Post-Disaster High-Resolution Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens., 2024
A Lightweight Dual-Branch Network for Building Change Detection in Remote Sensing Images Integrating Cross-Scale Coupling and Boundary Constraint.
IEEE Trans. Geosci. Remote. Sens., 2024
2023
Scale-Invariant Multi-Level Context Aggregation Network for Weakly Supervised Building Extraction.
Remote. Sens., March, 2023
ALNet: Auxiliary Learning-Based Network for Weakly Supervised Building Extraction From High-Resolution Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens., 2023
A Siamese Network Combining Multiscale Joint Supervision and Improved Consistency Regularization for Weakly Supervised Building Change Detection.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023
A Weakly Supervised Semantic Segmentation Approach for Damaged Building Extraction From Postearthquake High-Resolution Remote-Sensing Images.
IEEE Geosci. Remote. Sens. Lett., 2023
2022
MSG-SR-Net: A Weakly Supervised Network Integrating Multiscale Generation and Superpixel Refinement for Building Extraction From High-Resolution Remotely Sensed Imageries.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
PANet: Pixelwise Affinity Network for Weakly Supervised Building Extraction From High-Resolution Remote Sensing Images.
IEEE Geosci. Remote. Sens. Lett., 2022
2021
Building Damage Detection in Vhr Satellite Images Via Multi-Scale Scene Change Detection.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
2019
Deep Feature Fusion with Integration of Residual Connection and Attention Model for Classification of VHR Remote Sensing Images.
Remote. Sens., 2019
A Fine-Grained Fully Convolutional Network For Extraction of Building Along High-Speed Rail Lines from VHR Remote Sensing Image.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Detection of Vegetation Areas Attacked By Pests and Diseases Based on Adaptively Weighted Enhanced Global and Local Deep Features.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
2017
Robust Registration of Multimodal Remote Sensing Images Based on Structural Similarity.
IEEE Trans. Geosci. Remote. Sens., 2017
Topic Modelling for Object-Based Unsupervised Classification of VHR Panchromatic Satellite Images Based on Multiscale Image Segmentation.
Remote. Sens., 2017
IEEE Geosci. Remote. Sens. Lett., 2017
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017
2015
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015
Research on relationship between remote sensing image quality and performance of interest point detection.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015
2014
A Semisupervised Latent Dirichlet Allocation Model for Object-Based Classification of VHR Panchromatic Satellite Images.
IEEE Geosci. Remote. Sens. Lett., 2014
2013
A Multiscale Latent Dirichlet Allocation Model for Object-Oriented Clustering of VHR Panchromatic Satellite Images.
IEEE Trans. Geosci. Remote. Sens., 2013
2012
An object-oriented clustering algorithm for VHR panchromatic images using nonparametric latent Dirichlet allocation.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012