WP2.L409.2
MODELING HIERARCHICAL TOPOLOGICAL STRUCTURE IN SCIENTIFIC IMAGES WITH GRAPH NEURAL NETWORKS
Samuel Leventhal, Attila Gyulassy, Valerio Pascucci, University of Utah, United States of America; Mark Heimann, Lawrence Livermore National Laboratory, United States of America
Session:
WP2.L409: Graph Signal Processing and Machine Learning for Interpretable and robust image processing II Lecture
Track:
Special Sessions
Location:
Room 409
Presentation Time:
Wed, 11 Oct, 16:48 - 17:06 Malaysia Time (UTC +8)
Session Chair:
Yukihiro Bandoh, NTT
Session WP2.L409
WP2.L409.1: REALIZATION OF DIGRAPH FILTERS VIA AUGMENTED GFT
Hotaka Kitamura, Hiroyasu Yasuda, Niigata University, Japan; Yuichi Tanaka, Osaka University, Japan; Shogo Muramatsu, Niigata University, Japan
WP2.L409.2: MODELING HIERARCHICAL TOPOLOGICAL STRUCTURE IN SCIENTIFIC IMAGES WITH GRAPH NEURAL NETWORKS
Samuel Leventhal, Attila Gyulassy, Valerio Pascucci, University of Utah, United States of America; Mark Heimann, Lawrence Livermore National Laboratory, United States of America
WP2.L409.3: ROBUST GRAPH-BASED SEGMENTATION OF NOISY POINT CLOUDS
Pufan Li, Xiang Gao, Qianjiang Hu, Wei Hu, Peking University, China
WP2.L409.4: INTER-SCALE SURE-LET IMAGE RESTORATION WITH DEEP UNROLLED IMAGE PRIOR
Jikai Li, Shogo Muramatsu, Niigata University, Japan
WP2.L409.5: Introducing a Framework for Single-Human Tracking using Event-based Cameras
Dominik Eisl, Fabian Herzog, Technical University of Munich, Germany; Jean-Luc Dugelay, Eurecom, France; Ludovic Apvrille, Telecom Paris, France; Gerhard Rigoll, Technical University of Munich, Germany
Contacts