Chenying Liu

Orcid: 0000-0001-9172-3586

Affiliations:

Technical University of Munich, Data Science in Earth Observation, Germany
German Aerospace Center, Remote Sensing Technology Institute, Munich, Germany
Sun Yat-sen University, School of Geography and Planning, Guangzhou, China (former)

According to our database¹, Chenying Liu authored at least 21 papers between 2016 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

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Bibliography

2024

AIO2: Online Correction of Object Labels for Deep Learning With Incomplete Annotation in Remote Sensing Image Segmentation.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2024

Task Specific Pretraining with Noisy Labels for Remote sensing Image Segmentation.

[BibT_eX]

[DOI]

CoRR, 2024

2023

DeCUR: decoupling common & unique representations for multimodal self-supervision.

[BibT_eX]

[DOI]

Yi Wang

Conrad M. Albrecht

Nassim Ait Ali Braham

Chenying Liu

Zhitong Xiong

Xiao Xiang Zhu

CoRR, 2023

DeepLCZChange: A Remote Sensing Deep Learning Model Architecture for Urban Climate Resilience.

[BibT_eX]

[DOI]

CoRR, 2023

DeepLCZChange: A REMOTE SENSING DEEP LEARNING MODEL ARCHITECTURE FOR URBAN CLIMATE RESILIENCE<sup>CRediT</sup>.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022

Phase-Induced Gabor-Based Multiview Active Learning for Hyperspectral Image Classification.

[BibT_eX]

[DOI]

Runlin Cai

Chenying Liu

Jun Li

IEEE Geosci. Remote. Sens. Lett., 2022

SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation.

[BibT_eX]

[DOI]

Yi Wang

Nassim Ait Ali Braham

CoRR, 2022

Monitoring Urban Forests from Auto-Generated Segmentation MAPS.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

Deep Semantic Model Fusion for Ancient Agricultural Terrace Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2022

Peaks Fusion assisted Early-stopping Strategy for Overhead Imagery Segmentation with Noisy Labels.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Naive Gabor Networks for Hyperspectral Image Classification.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2021

Semisupervised Discriminative Random Field for Hyperspectral Image Classification.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Integrated Gabor-Based Decision Fusion for Hyperspectral Image Classification.

[BibT_eX]

[DOI]

Runlin Cai

Chenying Liu

Jun Li

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020

Hyperspectral Image Spectral-Spatial-Range Gabor Filtering.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2020

2019

Superpixel-Based Semisupervised Active Learning for Hyperspectral Image Classification.

[BibT_eX]

[DOI]

Chenying Liu

Jun Li

Lin He

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2019

Naive Gabor Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Accessibility-Free Active Learning for Hyperspectral Image Classification.

[BibT_eX]

[DOI]

Chenying Liu

Jun Li

Mercedes Eugenia Paoletti

Juan Mario Haut

Antonio Plaza

Qian Shi

Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

A New Spatio-Temporal Fusion Method for Remotely Sensed Data Based on Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018

Feature-Driven Active Learning for Hyperspectral Image Classification.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2018

Recent Advances on Spectral-Spatial Hyperspectral Image Classification: An Overview and New Guidelines.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2018

2016

Gabor-based active learning for hyperspectral image classification.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

Chenying Liu

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