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Ganchao Liu, Associate Professor

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Ganchao Liu, Associate Professor

Research Direction:Remote sensing image processing, Visual localization

Contact Address:P.O. Box 64, 127 West Youyi Road, Beilin District, Xi'an 710072, Shaanxi, P.R. China

Zip Code:710072

E-mail:liuganchao AT nwpu.edu.cn

Work Experience

2020.10-now Northwestern Polytechnical University Associate Professor
2018.10-2020.10 Northwestern Polytechnical University Postdoctral Research Fellow
2016.06-2018.10 Huawei Technologies Co., Ltd Algorithm Engineer

Representative Papers

  1. G. Liu*, Y. Zhang, Y. Dong, and X. Li*, “Style Transformation-Based Spatial-Spectral FeatureLearning for Unsupervised Change Detection,”IEEE Transactions on Geoscience and Remote Sensing,2022, 60, 5401515. doi: 10.1109/TGRS.2020.3026099.

  2. Y. Yuan, H. Ma, andG. Liu*, “Partial-DNet: A Novel Blind Denoising Model with Noise Intensity Estimation for HSI,”IEEE Transactions on Geoscience and Remote Sensing,Accepted. 2021.

  3. G. Liu,L. Li*, L. Jiao, Y. Dong*, and X. Li, “Stacked Fisher autoencoder for SAR change detection,”Pattern Recognition,2019, 96, 106971.[PDF]

  4. G. Liu*,H. Zhong, and L. Jiao, “Comparing Noisy Patches for Image Denoising: A Double Noise Similarity Model,”IEEE Transactions on Image Processing,2015, 24(3): 862~872.[PDF]

  5. G. Liu*L. Jiao, F. Liu, H. Zhong, and S. Wang, “A New Patch Based Change Detector for PolSAR Data,”Pattern Recognition,2015, 48(3): 685~695.[PDF]

Academic Service

  • He is a scientific and technological expert of Xi'an and a member of the remote sensing image professional committee of the Chinese Society of Image and Graphics (CSIG);

  • Served as reviewer of IEEE T-IP、IEEE T-GRS、IEEE T-NNLS、ISPRS J-PRS、Pattern Recognition and other internationally journals;

  • Served as track chair or PC member of dozens of international academic conferences such as IEEE ICICN, ACM MM, ACM ICMR, and AIPR.

Scientific Grants

  • As the leader, he presided over 10 Scientific Grants such as the National Natural Science Fund and the National Postdoctoral fund;

  • Participated in the national key R & D plan and Scientific and Technological Innovation 2030 "new generation artificial intelligence".

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