17 - 22 July, 2022 • Physical: Kuala Lumpur Convention Centre (KLCC), Kuala Lumpur, Malaysia • Hybrid: Online Platform

Preserving Our Heritage, Enabling Our Future Through Remote Sensing

17 - 22 July, 2022 • Physical: Kuala Lumpur Convention Centre (KLCC), Kuala Lumpur, Malaysia • Hybrid: Online Platform

MO6.V8.10

Unsupervised detection of ash dieback disease (Hymenoscyphus fraxineus) using diffusion-based hyperspectral image clustering

Sam Polk, Kangning Cui, James Murphy, Tufts University, United States; Aland Chan, David Coomes, University of Cambridge, United States; Robert Plemmons, Wake Forest University, United States
Session:
Classification and Clustering MMV IV Multimedia Virtual
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Location:
Virtual Room 8
Presentation Time:
Mon, 18 Jul, 21:35 - 22:45 Malaysia Time (UTC +8)
Mon, 18 Jul, 15:35 - 16:45 Central European Time (UTC +1)
Mon, 18 Jul, 13:35 - 14:45 UTC
Mon, 18 Jul, 09:35 - 10:45 Eastern Time (UTC -5)
Session Co-Chairs:
Sam Polk, Tufts University and Weiwei Song, Peng Cheng Laboratory
Session Manager:
Wei Pin, Peter Choo
Presentation
Discussion
Resources
No resources available.
Session MO6.V8
MO6.V8.1: AN ATTENTION BASED LIGHTWEIGHT NETWORK FOR HYPERSPECTRAL IMAGES
Xuming Zhang, Qingjiu Tian, Nanjing University, China; Xingfa Gu, Aerospace Information Research Institute, Chinese Academy of Sciences, China
MO6.V8.2: FEW-SHOT HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON DOMAIN ADAPTATION OF CLASS BALANCE
Qi Zhen, Xiangrong Zhang, Zhenyu Li, Biao Hou, Xu Tang, Licheng Jiao, Xidian University, China; Li Gao, State Key Laboratory of Geo-Information Engineering, China
MO6.V8.3: CNN Based Target Classification Framework based on Complex Sparse SAR Image: Initial Result
Jiarui Deng, Zehao Liu, Jingjing Zhang, Hui Bi, Nanjing University of Aeronautics and Astronautics, China
MO6.V8.4: ADAPTED ELBOW METHOD FOR SPHERICAL CLUSTERING OF FRACTURE DATA FROM DIGITAL OUTCROP MODEL
Graciela Racolte, Ademir Marques Jr, Luiz Gonzaga Jr, Mauricio Veronez, Unisinos University, Brazil; Caroline Cazarin, Petrobras, Brazil
MO6.V8.5: CONVOLUTION ENHANCED SPATIAL-SPECTRAL UNIFIED TRANSFORMER NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Ziqi Xin, Zhongwei Li, Mingming Xu, Leiquan Wang, Xue Zhu, China University Of Petroleum(East China), China
MO6.V8.6: DISCRIMINATIVE FEATURE EXTRACTION AND FUSION FOR CLASSIFICATION OF HYPERSPECTRAL AND LIDAR DATA
Weiwei Song, Peng Cheng Laboratory, China; Zhi Gao, Yongjun Zhang, Wuhan University, China
MO6.V8.7: AMPLITUDE SCINTILLATION FORECASTING USING BAGGED TREES
Abdollah Darya, Aisha Al-Owais, Muhammad Shaikh, Ilias Fernini, University of Sharjah, United Arab Emirates
MO6.V8.8: EXPLORING DIFFERENT LEVELS OF CLASS NOMENCLATURE IN RANDOM FOREST CLASSIFICATION OF SENTINEL-2 DATA
Daniel Moraes, Pedro Benevides, Hugo Costa, Francisco D. Moreira, Mário Caetano, Direção-Geral do Território, Portugal
MO6.V8.9: UNSUPERVISED DEEP EMBEDDING CLUSTERING FOR AIS TRAJECTORY
Lian Xiong, Xuanrui Xiong, Fan Zhang, Chongqing University of Posts and Telecommunications, China; Huaixin Chen, University of Electronic Science and Technology of China, China
MO6.V8.10: Unsupervised detection of ash dieback disease (Hymenoscyphus fraxineus) using diffusion-based hyperspectral image clustering
Sam Polk, Kangning Cui, James Murphy, Tufts University, United States; Aland Chan, David Coomes, University of Cambridge, United States; Robert Plemmons, Wake Forest University, United States