The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Deep learning-based Wood Reconstruction and Leaf-Wood segmentation model for full tree volume estimation from 3D Tree Modeling under Presence of Occlusions and Leaves (AGU25)

Deep learning-based Wood Reconstruction and Leaf-Wood segmentation model for full tree volume estimation from 3D Tree Modeling under Presence of Occlusions and Leaves

Heeju Mun1, Youngryel Ryu1, Tackang Yang2, Yunsoo Nam3 and Dr. Changhyun Choi4, (1)Seoul National University, Department of Landscape Architecture and Rural Systems Engineering, Seoul, South Korea, (2)Seoul National University, Interdisciplinary Program in Lanscape Architecture, Seoul, Korea, Republic of (South), (3)Seoul National University, Department of Lanscape Architecture and Rural Systems Engineering, Seoul, Korea, Republic of (South), (4)Inha University, Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea, Seoul, South Korea