FRP.P7.3

AN ITERATIVE METHOD FOR HYPERSPECTRAL PIXEL UNMIXING LEVERAGING LATENT DIRICHLET VARIATIONAL AUTOENCODER

Kiran Mantripragada, Ontario Tech University, Canada; Paul R. Adler, United States Department of Agriculture, Canada; Peder A. Olsen, Microsoft Research, Canada; Faisal Z. Qureshi, Ontario Tech University, Canada
Session:
FRP.P7: Hyperspectral Unmixing Poster
Track:
Data Analysis
Location:
Poster Area 7
Presentation Time:
Fri, 21 Jul, 14:15 - 15:45 Pacific Time (UTC -8)
Session Chair:
Miguel Velez-Reyes, The University of Texas at El Paso
Session Managers:
Srashti Singh and NIMA ESMAEILZADEH and Suhaimee Buya and sunni kanta prasad kushwaha
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Session FRP.P7
FRP.P7.1: A SPECTRAL–SPATIAL ATTENTION AUTOENCODER NETWORK FOR HYPERSPECTRAL UNMIXING
Jie Wang, Jindong Xu, Yantai University, China
FRP.P7.2: COLLABORATIVE CONSISTENCY AUTOENCODER HYPERSPECTRAL UNMIXING USING DEEP IMAGE PRIOR
Min Huang, Nanchang Institute of Technology, China; Mengxiong Tang, GMC Building, China; Fan Li, Shaoquan Zhang, Shengqian Wang, Ningyuan Zhang, Chengzhi Deng, Nanchang Institute of Technology, China
FRP.P7.3: AN ITERATIVE METHOD FOR HYPERSPECTRAL PIXEL UNMIXING LEVERAGING LATENT DIRICHLET VARIATIONAL AUTOENCODER
Kiran Mantripragada, Ontario Tech University, Canada; Paul R. Adler, United States Department of Agriculture, Canada; Peder A. Olsen, Microsoft Research, Canada; Faisal Z. Qureshi, Ontario Tech University, Canada
FRP.P7.4: A DUAL-STREAM CONVOLUTIONAL FEATURE FUSION NETWORK FOR HYPERSPECTRAL UNMIXING
Haoyue Hua, Jie Li, Ying Wang, Xinbo Gao, Xidian University, China
FRP.P7.5: A NOVEL LINEAR MIXING MODEL ADDRESSING SPECTRAL-SPATIAL INTRA-CLASS VARIABILITY WITH AN ASSOCIATED PENALIZED NMF-BASED HYPERSPECTRAL UNMIXING ALGORITHM
Moussa Sofiane Karoui, Fatima Zohra Benhalouche, Agence Spatiale Algérienne, Algeria; Yannick Deville, Université de Toulouse, France
FRP.P7.6: NEW INFORMED LINEAR MIXING MODEL AND NMF-BASED UNMIXING METHOD ADDRESSING SPECTRAL VARIABILITY WITH AN APPLICATION TO MINERAL DETECTION AND MAPPING USING PRISMA HYPERSPECTRAL REMOTE SENSING DATA
Fatima Zohra Benhalouche, Oussama Benabbou, Oualid Yahia, Moussa Sofiane Karoui, Agence Spatiale Algérienne, Algeria; Yannick Deville, Université de Toulouse, France; Lahsen Wahib Kebir, Ahmed Bennia, Agence Spatiale Algérienne, Algeria
FRP.P7.7: UNMIXING ANALYSIS OF CLOSE-RANGE HYPERSPECTRAL IMAGES
Ana Chavez-Lopez, Miguel Velez-Reyes, The University of Texas at El Paso, United States
FRP.P7.8: A SHUFFLED DILATED CONVOLUTIONAL NEURAL NETWORK FOR HYPERSPECTRAL IMAGE USING TRANSFER LEARNING
Koushikey Chhapariya, Krishna Mohan Buddhiraju, IIT Bombay, India; Anil Kumar, IIRS, ISRO, India
FRP.P7.9: WAVELET TRANSFORM BASED NETWORK FOR SPECTRAL SUPER-RESOLUTION
Weixin Ren, Qianyue Duan, Tiange Huang, Lei Zhang, Wei Wei, Northwestern Polytechnical University, China; Chen Ding, Xi’an University of Posts and Telecommunications, China; Yanning Zhang, Northwestern Polytechnical University, China
FRP.P7.10: PIXEL- AND PATCH-WISE CONTEXT-AWARE LEARNING WITH CNN AND GCN COLLABORATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Hong Wang, Kun Gao, Xiaodian Zhang, Junwei Wang, Zibo Hu, Zhijia Yang, Beijing Institute of technology, China; Yuxuan Mao, Beijing Institute of Technology, China; Yutong Liu, Beijing Institute of technology, China
FRP.P7.11: GL-NET:GAUSSIAN LEADING NETWORK FOR SAR SHIP DETECTION
Zenghao Chen, Yanan You, Wenli Zhou, Meng Gang, Beijing University of Posts and Telecommunications, China
FRP.P7.12: HYBRID TRANSFORMER NETWORK FOR CHANGE DETECTION UNDER SELF-SUPERVISED PRETRAINING
Yongjing Cui, Yin Zhuang, Shan Dong, Xinyi Zhang, Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Beijing Institute of Technology, China; Peng Gao, Shanghai AI Laboratory, China; He Chen, Liang Chen, Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Beijing Institute of Technology, China
Resources
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