MLSP-L10.6
PHYSICS-INFORMED NEURAL NETWORKS FOR OCEAN ACOUSTIC FIELD RECONSTRUCTION AND SOURCE LOCALIZATION
YONGSUNG PARK, Woods Hole Oceanographic Institution, United States of America
Session:
MLSP-L10: Deep Learning Models for Structured Signal Processing Oral
Track:
Machine Learning for Signal Processing [ML]
Location:
Room 117
Presentation Time:
Wed, 6 May, 10:40 - 11:00
Presentation
Discussion
Resources
No resources available.
Session MLSP-L10
MLSP-L10.1: HyperFedFS: Heterogeneous Federated Few-Shot Learning with Hypergraph-driven Collaborative Aggregation
Qi Tan, Zongze Wu, Shenzhen University, China
MLSP-L10.2: AERIS-RTDETR: ULTRASOUND-AWARE REAL-TIME DETECTION WITH ORTHOGONAL ANISO-SCALE BLOCKS AND ECHOGENICITY-GUIDED FUSION
Fan Liu, Jiangtao Wang, Qing Zhang, East China Normal University, China; Yukun Zhang, Zhengzhou University, China; Hailin Pan, East China Normal University, China
MLSP-L10.3: DUALEXPERTNET: DISPARITY-AWARE SEMANTIC-DETAIL COMPLEMENTARITY FOR CAMOUFLAGED OBJECT DETECTION
Qiang Yu, Qing Zhang, Jingming Wang, Jiayun Wu, Shanghai Institute of Technology, China; Sheng-hua Zhong, Shenzhen University, China
MLSP-L10.4: Reg3D: Reconstructive Geometry Instruction Tuning for 3D Scene Understanding
Hongpei Zheng, Lintao Xiang, Lin Qian, Zhenghao Li, Qijun Yang, Hujun Yin, University of Manchester, United Kingdom of Great Britain and Northern Ireland
MLSP-L10.5: UniSTFormer: Unified Spatio-Temporal Lightweight Transformer for Efficient Skeleton-Based Action Recognition
Wenhan Wu, University of North Carolina at Charlotte, United States of America; Zhishuai Guo, Northern Illinois University, United States of America; Chen Chen, University of Central Florida, United States of America; Aidong Lu, University of North Carolina at Charlotte, United States of America
MLSP-L10.6: PHYSICS-INFORMED NEURAL NETWORKS FOR OCEAN ACOUSTIC FIELD RECONSTRUCTION AND SOURCE LOCALIZATION
YONGSUNG PARK, Woods Hole Oceanographic Institution, United States of America
Contacts