Ning Li
Orcid: 0000-0002-7212-6783Affiliations:
- Nanjing University, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, School of Geography and Ocean Science, Nanjing, China
According to our database1,
Ning Li
authored at least 18 papers
between 2019 and 2025.
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Bibliography
2025
A Multicomponent Collaborative Fossil Fuel Power Plants Detection Framework Based on Geographic Analysis in Wide Areas.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025
RCSD-UAV: An object detection dataset for unmanned aerial vehicles in realistic complex scenarios.
Eng. Appl. Artif. Intell., 2025
2024
Evaluation of Ten Deep-Learning-Based Out-of-Distribution Detection Methods for Remote Sensing Image Scene Classification.
Remote. Sens., May, 2024
Robust Land Cover Classification With Local-Global Information Decoupling to Address Remote Sensing Anomalous Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024
Automatic labelling framework for optical remote sensing object detection samples in a wide area using deep learning.
Expert Syst. Appl., 2024
SDG: A global large-scale airport perception disparity cognition modeling method based on deep learning and geographic knowledge.
Eng. Appl. Artif. Intell., 2024
2023
Large dam candidate region identification from multi-source remote sensing images via a random forest and spatial analysis approach.
Int. J. Digit. Earth, December, 2023
Study on Road Network Vulnerability Considering the Risk of Landslide Geological Disasters in China's Tibet.
Remote. Sens., September, 2023
S&GDA: An Unsupervised Domain Adaptive Semantic Segmentation Framework Considering Both Imaging Scene and Geometric Domain Shifts.
IEEE Trans. Geosci. Remote. Sens., 2023
Eng. Appl. Artif. Intell., 2023
2022
Structure-Aware Weakly Supervised Network for Building Extraction From Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens., 2022
Verification of Dam Spatial Location in Open Datasets Based on Geographic Knowledge and Deep Learning.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
Framework for Runway's True Heading Extraction in Remote Sensing Images Based on Deep Learning and Semantic Constraints.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
2021
Framework for Unknown Airport Detection in Broad Areas Supported by Deep Learning and Geographic Analysis.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021
Validation of Global Airport Spatial Locations From Open Databases Using Deep Learning for Runway Detection.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021
Detecting unknown dams from high-resolution remote sensing images: A deep learning and spatial analysis approach.
Int. J. Appl. Earth Obs. Geoinformation, 2021
2019
Remote. Sens., 2019