Xin Luo

Orcid: 0000-0002-9534-592X

Affiliations:
  • University of Electronic Science and Technology of China, Yangtze Delta Region Institute, School of Resources and Environment, Huzhou, China


According to our database1, Xin Luo authored at least 12 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Fast Automatic Registration of UAV Images via Bidirectional Matching.
Sensors, October, 2023

Impact of Training Data Size on Classifiers When Coarse Resolution Imageries Were Used for Regional Land Cover Mapping.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022
Multi-Angle Optical Image Automatic Registration by Combining Point and Line Features.
Sensors, 2022

SI-SA GAN: A Generative Adversarial Network Combined With Spatial Information and Self-Attention for Removing Thin Cloud in Optical Remote Sensing Images.
IEEE Access, 2022

2021
Research on Change Detection Method of High-Resolution Remote Sensing Images Based on Subpixel Convolution.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Satellite-Borne Optical Remote Sensing Image Registration Based on Point Features.
Sensors, 2021

UAV Remote Sensing Image Automatic Registration Based on Deep Residual Features.
Remote. Sens., 2021

Boundary-Aware Refined Network for Automatic Building Extraction in Very High-Resolution Urban Aerial Images.
Remote. Sens., 2021

2020
Fast Automatic Vehicle Detection in UAV Images Using Convolutional Neural Networks.
Remote. Sens., 2020

GSCA-UNet: Towards Automatic Shadow Detection in Urban Aerial Imagery with Global-Spatial-Context Attention Module.
Remote. Sens., 2020

Research on Vehicle Detection Based on Faster R-CNN for UAV Images.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Research on Stereo Matching for Satellite Generalized Image Pair Based on Improved SURF and RFM.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020


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