Task-Adaptive Embedding Learning with Dynamic Kernel Fusion for Few-Shot Remote Sensing Scene Classification

Task-Adaptive Embedding Learning with Dynamic Kernel Fusion for Few-Shot Remote Sensing Scene Classification

The central goal of few-shot scene classification is to learn a model that can generalize well to a novel scene category (UNSEEN) from only one or a few labeled examples. Recent works in the Remote Sensing (RS) community tackle this challenge by developing algorithms in a meta-learning manner. Howev...

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Bibliographic Details
Main Authors: Pei Zhang, Guoliang Fan, Chanyue Wu, Dong Wang, Ying Li
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Remote Sensing
Subjects:
remote-sensing classification
scene classification
few-shot learning
meta-learning
vision transformers
multiscale feature fusion
Online Access:https://www.mdpi.com/2072-4292/13/21/4200

Internet

https://www.mdpi.com/2072-4292/13/21/4200

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