Lijun Zhao

Orcid: 0000-0002-7140-8105

Affiliations:
  • Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China (PhD 2015)


According to our database1, Lijun Zhao authored at least 12 papers between 2014 and 2022.

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

Timeline

Legend:

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PhD thesis 
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Bibliography

2022
Few-Shot Object Detection of Remote Sensing Images via Two-Stage Fine-Tuning.
IEEE Geosci. Remote. Sens. Lett., 2022

2021
WTS: A Weakly towards Strongly Supervised Learning Framework for Remote Sensing Land Cover Classification Using Segmentation Models.
Remote. Sens., 2021

Increasing Shape Bias to Improve the Precision of Center Pivot Irrigation System Detection.
Remote. Sens., 2021

2019
Remote Sensing Image Scene Classification Using CNN-CapsNet.
Remote. Sens., 2019

Analysis of the inter-dataset representation ability of deep features for high spatial resolution remote sensing image scene classification.
Multim. Tools Appl., 2019

SiftingGAN: Generating and Sifting Labeled Samples to Improve the Remote Sensing Image Scene Classification Baseline In Vitro.
IEEE Geosci. Remote. Sens. Lett., 2019

A Comparative Study of U-Nets with Various Convolution Components for Building Extraction.
Proceedings of the Joint Urban Remote Sensing Event, 2019

Improved Visual Vocabularies for Scene Classification of High Resolution Remote Sensing Imagery in Urban Areas.
Proceedings of the Joint Urban Remote Sensing Event, 2019

Application Potential of GF-4 Satellite Images for Water Body Extraction.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2016
Hyperspectral image classification with sparse representation classifier and active learning.
Proceedings of the 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2016

2014
Land-Use Scene Classification Using a Concentric Circle-Structured Multiscale Bag-of-Visual-Words Model.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014

A novel semisupervised transductive SVM with spatial similarity for classification of hyperspectral data.
Proceedings of the 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014


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