TU2.P9.3
MULTI-TASK LEARNING WITH MULTI-ANNOTATION TRIPLET LOSS FOR IMPROVED OBJECT DETECTION
Meilun Zhou, Aditya Dutt, Alina Zare, University of Florida, United States
Session:
TU2.P9: Hyperspectral and Multspectral Object Detection Oral
Track:
Data Analysis
Location:
Plaza: Room P9
Presentation Time:
Tuesday, 5 August, 11:00 - 11:15
Session Co-Chairs:
Stefania Matteoli, National Research Council (CNR) and Yubo Ma, University of Electronic Science and Technology of China
Session TU2.P9
TU2.P9.1: A Joint Framework for Underwater Hyperspectral Image Restoration and Target Detection With Conditional Diffusion Model
Qi Li, Jinghua Li, Tong Li, Yan Feng, Northwestern Polytechnical University, China
TU2.P9.2: TARGET-CONSTRAINED GAUSSIAN MIXTURE MODEL FOR HYPERSPECTRAL DETECTION
Yubo Ma, University of Electronic Science and Technology of China, China; Siyu Cai, Qingke Zou, Sichuan University, China
TU2.P9.3: MULTI-TASK LEARNING WITH MULTI-ANNOTATION TRIPLET LOSS FOR IMPROVED OBJECT DETECTION
Meilun Zhou, Aditya Dutt, Alina Zare, University of Florida, United States
TU2.P9.4: CFAR Vessel Detection in PRISMA Hyperspectral Images
Salvatore Maresca, Stefania Matteoli, National Research Council (CNR), Italy
TU2.P9.5: UNSUPERVISED DETECTION OF RED TIDES IN SATELLITE IMAGERY BASED ON SPATIAL-SPECTRAL INFORMATION FUSION
Qiong Wu, Xudong Kang, Zihao Wang, Puhong Duan, Shutao Li, Hunan university, China
Resources