Baisen Liu

According to our database, Baisen Liu authored at least 21 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Open-Set Cross-Domain Hyperspectral Image Classification Based on Manifold Mapping Alignment.

Xiangrong Zhang, Baisen Liu

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

Instructional Mask Autoencoder: A Scalable Learner for Hyperspectral Image Classification.

Weili Kong, Baisen Liu, Xiaojun Bi, Jiaming Pei, Zheng Chen

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

A Universal Representation Mechanism for Multisource Remote Sensing Image.

Weili Kong, Baisen Liu, Xiaojun Bi, Yihan He

IEEE Geosci. Remote. Sens. Lett., 2024

A Shared Encoder for Multi-Source Hyperspectral Images.

Weili Kong, Baisen Liu, Xiaojun Bi, Jiaming Pei

Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

2023

Spectral Swin Transformer Network for Hyperspectral Image Classification.

Baisen Liu, Yuanjia Liu, Wulin Zhang, Yiran Tian, Weili Kong

Remote. Sens., August, 2023

A New Method for False Alarm Suppression in Heterogeneous Change Detection.

Cong Xu, Baisen Liu, Zishu He

Remote. Sens., April, 2023

A Normalized Spatial-Spectral Supervoxel Segmentation Method for Multispectral Point Cloud Data.

Likun Chen, Yanfeng Gu, Xian Li, Xiangrong Zhang, Baisen Liu

IEEE Trans. Geosci. Remote. Sens., 2023

Fusing 3D-CNN and lightweight Swin Transformer networks for HSI.

Baisen Liu, Yuanjia Liu, Wulin Zhang, Yiran Tian

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

A Scalable Self-supervised Learner for Hyperspectral Image Classification.

Weili Kong, Lin Qi, Baisen Liu, Jiaming Pei

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Talent Flow Model Based on Graph Attention Network.

Baisen Liu, Zongting Jia, Lili Zhao, Weili Kong

Proceedings of the 4th International Conference on Big Data & Artificial Intelligence & Software Engineering, 2023

2022

Multitemporal Intrinsic Image Decomposition With Temporal-Spatial Energy Constraints for Remote Sensing Image Analysis.

Guoming Gao, Baisen Liu, Xiangrong Zhang, Xudong Jin, Yanfeng Gu

IEEE Trans. Geosci. Remote. Sens., 2022

2020

Bayesian robust estimation of partially functional linear regression models using heavy-tailed distributions.

Guodong Shan, Yiheng Hou, Baisen Liu

Comput. Stat., 2020

Testing proportionality of two high-dimensional covariance matrices.

Guanghui Cheng, Baisen Liu, Guo-Liang Tian, Shurong Zheng

Comput. Stat. Data Anal., 2020

2019

Unsupervised Multitemporal Domain Adaptation With Source Labels Learning.

Baisen Liu, Guoming Gao, Yanfeng Gu

IEEE Geosci. Remote. Sens. Lett., 2019

Bayesian inference of mixed-effects ordinary differential equations models using heavy-tailed distributions.

Baisen Liu, Liangliang Wang, Yunlong Nie, Jiguo Cao

Comput. Stat. Data Anal., 2019

2018

Supervised functional principal component analysis.

Yunlong Nie, Liangliang Wang, Baisen Liu, Jiguo Cao

Stat. Comput., 2018

Bayesian estimation of ordinary differential equation models when the likelihood has multiple local modes.

Baisen Liu, Liangliang Wang, Jiguo Cao

Monte Carlo Methods Appl., 2018

2017

Estimating functional linear mixed-effects regression models.

Baisen Liu, Liangliang Wang, Jiguo Cao

Comput. Stat. Data Anal., 2017

2014

A new test for the proportionality of two large-dimensional covariance matrices.

Baisen Liu, Lin Xu, Shurong Zheng, Guo-Liang Tian

J. Multivar. Anal., 2014

Testing proportionality of two large-dimensional covariance matrices.

Lin Xu, Baisen Liu, Shurong Zheng, Shaokun Bao

Comput. Stat. Data Anal., 2014

2013

Improved principal component analysis based hyperspectral image compression method.

Baisen Liu, Ye Zhang, Wulin Zhang

Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013