TU2.R13.1
SEMANTIC-DRIVEN GRAPH REASONING WITH LIGHTWEIGHT AGGREGATION FOR HSI-LIDAR/SAR IMAGE JOINT CLASSIFICATION
Jiaqi Yang, Min Chen, University of Wisconsin–Madison, United States
Session:
TU2.R13: Attention and Graph Models for Image Classification Oral
Track:
Theory and Techniques
Location:
TBD
Presentation Time:
Tue, 11 Aug, 11:00 - 11:15
Presentation
Discussion
Resources
No resources available.
Session TU2.R13
TU2.R13.1: SEMANTIC-DRIVEN GRAPH REASONING WITH LIGHTWEIGHT AGGREGATION FOR HSI-LIDAR/SAR IMAGE JOINT CLASSIFICATION
Jiaqi Yang, Min Chen, University of Wisconsin–Madison, United States
TU2.R13.2: A ROBUST GRAPH-BASED FRAMEWORK FOR ACCURATE FIRST ARRIVAL PICKING IN SEISMIC EXPLORATION
Musab Alsheikh, Wail Mousa, King Fahd University of Petroleum and Minerals, Saudi Arabia
TU2.R13.3: Enhancing Multi-label Scene Classification using Novel Co-occurrence Aware Loss Functions in Remote Sensing Images
Shreyansh Aswal, Ushasi Chaudhuri, Shailesh Deshpande, Tata Consultancy Services Ltd, India
TU2.R13.4: HISTOGRAM-BASED PARAMETER-EFFICIENT TUNING FOR PASSIVE AND ACTIVE SONAR CLASSIFICATION
Amirmohammad Mohammadi, Texas A&M University, United States; Davelle Carreiro, Alexandra Van Dine, Massachusetts Institute of Technology Lincoln Laboratory, United States; Joshua Peeples, Texas A&M University, United States
Contacts