WE1.R13.4
DUAL-DOMAIN FEATURE REPRESENTATION BASED CONTRASTIVE NETWORK FOR FEW-SHOT HYPERSPECTRAL IMAGE CLASSIFICATION
Rujun Zhang, Wenming Cao, Shenzhen University, China; Qifan Liu, Shenzhen Polytechnic University, China
Session:
WE1.R13: Unsupervised, Few Shot, and Transfer Learning Oral
Track:
Theory and Techniques
Location:
TBD
Presentation Time:
Wed, 12 Aug, 09:15 - 09:30
Presentation
Discussion
Resources
No resources available.
Session WE1.R13
WE1.R13.1: DEEP SPATIALLY-REGULARIZED AND SUPERPIXEL-BASED DIFFUSION LEARNING FOR UNSUPERVISED HYPERSPECTRAL IMAGE CLUSTERING
Vutichart Buranasiri, James Murphy, Tufts University, United States
WE1.R13.2: CLUSTERING NDVI TIME SERIES TO ESTIMATE PHENOLOGY CURVES IN NORTHWESTERN MEXICAN ARID MANGROVES
Inder Tecuapetla-Gómez, Secretaria de Ciencias, Humanidades, Tecnología e Innovación (SECIHTI), Mexico; Samuel Velázquez-Salazar, Comisión Nacional para el Conocimiento y Uso de la Biodiversidad, Mexico
WE1.R13.3: MHH-PROTONET: LEVERAGING HIERARCHICAL LABEL ONTOLOGY FOR ENHANCED FEW-SHOT SCENE CLASSIFICATION
Keli Cheng, Northwest Missouri State University, United States; Grant Scott, University of Missouri, United States; Weipeng Wu, Northwest Missouri State University, United States
WE1.R13.4: DUAL-DOMAIN FEATURE REPRESENTATION BASED CONTRASTIVE NETWORK FOR FEW-SHOT HYPERSPECTRAL IMAGE CLASSIFICATION
Rujun Zhang, Wenming Cao, Shenzhen University, China; Qifan Liu, Shenzhen Polytechnic University, China
Contacts