TU2.R8.3

XAI for Early Crop Classification

Ayshah Chan, Maja Schneider, Marco Körner, Technical University of Munich, Germany
Session:
TU2.R8: Forest and Vegetation Mapping Through Machine Learning Methods Oral
Track:
Land Applications
Location:
Room H
Presentation Time:
Tue, 18 Jul, 10:39 - 10:51 Pacific Time (UTC -8)
Session Co-Chairs:
Sassan Saatchi, California Institute of Technology and Yuei-An Liou, National Central University
Session Manager:
Lanying Wang
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Session TU2.R8
TU2.R8.1: MAPPING CALIFORNIA'S FORESTS WITH PLANETSCOPE'S VISUAL IMAGERY: A DEEP LEARNING APPROACH
Griffin Carter, Fabien Wagner, Ricardo Dalagnol, Sophie Roberts, CTrees, United States
TU2.R8.2: DELVE INTO THE IMPACT OF OBJECT’S LOCATION INTELLIGENCE ON THE SPECIES DISTRIBUTION MODELING VIA DEEP LEARNING
Chin-Jin Kuo, Chung-Hsing University, Taiwan; Bao-Hua Shao, Forest Bureau, Taiwan; Nan-Chang Lo, Kai-Yi Huang, Chung-Hsing University, Taiwan
TU2.R8.3: XAI for Early Crop Classification
Ayshah Chan, Maja Schneider, Marco Körner, Technical University of Munich, Germany
TU2.R8.4: MAPPING TREE MORTALITY IN CALIFORNIA FROM VERY HIGH RESOLUTION IMAGERY USING DEEP LEARNING
Yan Cheng, Stefan Oehmcke, Martin Brandt, University of Copenhagen, Denmark; Adrian Das, Lisa Rosenthal, US Geological Survey, United States; Sassan Saatchi, Fabien Wagner, California Institute of Technology, United States; Anton Vrieling, University of Twente, Netherlands; Wim Verbruggen, Claus Beier, Stephanie Horion, University of Copenhagen, Denmark
TU2.R8.5: FOREST BIOPHYSICAL PARAMETER ESTIMATION VIA MACHINE LEARNING AND NEURAL NETWORK APPROACHES
Samet Aksoy, Istanbul Technical University, Turkey; Shouq Zuhter Hasan Al Shwayyat, Marmara University, Turkey; Şule Nur Topgül, Elif Sertel, Istanbul Technical University, Turkey; Cem Ünsalan, Marmara University, Turkey; Jari Salo, University of Helsinki, Finland; Anton Holmström, Katam Technologies, Sweden; Jörgen Wallerman, Mats Nilsson, Swedish University of Agricultural Sciences, Sweden; Johan E.S. Fransson, Linnaeus University, Sweden
Resources
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