MOPB.PA.27

A SPECTRAL VARIABILITY ATTENTION AUTOENCODER NETWORK FOR HYPERSPECTRAL UNMIXING

Shu Xiang, Xiaorun Li, Shuhan Chen, Zhejiang University, China
Session:
MOPB.PA: Hyperspectral Data Processing and Analysis I Poster
Track:
Data Analysis
Location:
Poster Area 4: Trianti Balcony
Presentation Time:
Mon, 8 Jul, 15:20 - 16:20
Session Chair:
Licheng Jiao, Xidian University
Presentation
Discussion
Resources
No resources available.
Session MOPB.PA
MOPB.PA.20: SPECTRAL FEATURE ANALYSIS FOR ENDMEMBER DETECTION IN CUPRITE HILLS WITH EMIT DATA
Morteza Safari, Stony Brook University, United States; Marziyeh Safari, University of Bergen, Norway
MOPB.PA.21: SPECTRAL-SPATIAL DUAL-BRANCH CROSS-ENHANCED TRANSFORMER FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Hang Zhang, Nanjing University of Information Science and Technology, China; Tianming Zhan, Nanjing Audit University, China; Le Sun, Nanjing University of Information Science and Technology, China
MOPB.PA.22: SPATIAL-SPECTRAL TWIN AUTOENCODERS FOR HYPERSPECTRAL UNMIXING VIA SUPERPIXEL-HYPERGRAPH-AUGMENTED FEATURE REPRESENTATION
Bin Yang, Zexing Zhang, Donghua University, China
MOPB.PA.23: Assessing the Adaptability of Self-Supervised Learning Methods for Small-Scale Hyperspectral Imaging
Andrea Potì, Sapienza University of Rome, Italy; Valerio Marsocci, KU Leuven, Belgium; Alessandro Nicolosi, Leonardo Labs, Italy; Simone Scardapane, Sapienza University of Rome, Italy
MOPB.PA.24: SPATIAL-SPECTRAL DIFFERENCE CONSTRAINT UNDER LOW-RANK TENSOR FACTORIZATION FOR HSI MIXED NOISE REMOVAL
Yaming Zheng, Qiang Zhang, Jian Zhu, Dalian Maritime University, China
MOPB.PA.25: AN AUTOENCODER FRAMEWORK WITH TRANSFORMER ENCODER AND EMLM EMBEDDED DECODER FOR NONLINEAR HYPERSPECTRAL ANOMALY DETECTION
Ziyu Wu, Linwei Li, Bin Wang, Bo Hu, Fudan University, China
MOPB.PA.26: UNSUPERVISED NONLINEAR HYPERSPECTRAL UNMIXING BASED ON AN EXTENDED MULTILINEAR MIXING MODEL-INSPIRED DUAL-STREAM NETWORK
Minglei Li, Linwei Li, Bin Wang, Bo Hu, Fudan University, China
MOPB.PA.27: A SPECTRAL VARIABILITY ATTENTION AUTOENCODER NETWORK FOR HYPERSPECTRAL UNMIXING
Shu Xiang, Xiaorun Li, Shuhan Chen, Zhejiang University, China
MOPB.PA.28: GRAPH LAPLACIAN REGULARIZATION AND LOCAL COLLABORATIVE SPARSE REGRESSION BASED ON SUPERPIXEL SEGMENTATION FOR HYPERSPECTRAL IMAGERY
Qishen Yang, Ruyi Feng, Lizhe Wang, Hui Luo, School of Computer Science, China University of Geosciences, P. R. China, China
MOPB.PA.29: SUBPIXEL TARGET DETECTION BASED ON A DEEP NEURAL NETWORK
Edisanter Lo, Susquehanna University, United States
MOPB.PA.30: CONSISTENCY-AWARE CUSTOMIZED LEARNING FOR CROSS-SCENE HYPERSPECTRAL IMAGE CLASSIFICATION
Kexin Ding, Ting Lu, Yuxin Fang, Shutao Li, Hunan University, China
MOPB.PA.31: CNN and Transformer Hybrid Network for Hyperspectral Image Classification
Zhaobin Wang, Yan Li, Zhongxin Cheng, Lanzhou University, China; Yaonan Zhang, Northwest Institute of Eco-Environment and Resources, CAS, China
MOPB.PA.32: DIFFERENTIAL FEATURE-ENHANCED FUSION NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Qingwang Wang, Jiangbo Huang, Pengcheng Jin, Yebo Gu, Tao Shen, Kunming University of Science and Technology, China
MOPB.PA.33: UNIVERSAL DOMAIN ADAPTATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Qingmei Li, Peking University, China; Yibin Wen, Juepeng Zheng, Sun Yat-Sen University, China; Yuxiang Zhang, Beijing Institute of Technology, China; Haohuan Fu, Tsinghua University, China
MOPB.PA.34: CENTER MASK SELF-ATTENTION NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Yizhou Zou, Xu Tang, Yue Ma, Jingjing Ma, Cheng Zhu, Xiangrong Zhang, Licheng Jiao, Xidian University, China
MOPB.PA.35: BAND EMBEDDING-BASED NETWORK FOR SPECTRAL SUPER-RESOLUTION
Meimei Weng, Jianjun Liu, Jiangnan University, China
MOPB.PA.36: DUAL-BRANCH AUTOENCODER WITH CLUSTERING INFORMATION FOR HYPERSPECTRAL BLIND UNMIXING
Hongru Zong, Jianjun Liu, Jiangnan University, China
MOPB.PA.37: THIN CLOUD CORRECTION FOR OPTICAL SATELLITE IMAGES VIA SIMILAR PIXEL REPLACEMENT WITH SHORT-WAVE INFRARED BAND AS GUIDANCE
Chi Zhang, Yang Liu, Huagui He, Peng Yi, Guangzhou Urban Planning & Design Survey Research Institute, China
Resources
No resources available.