Meta-FSEO: A Meta-Learning Fast Adaptation with Self-Supervised Embedding Optimization for Few-Shot Remote Sensing Scene Classification

Meta-FSEO: A Meta-Learning Fast Adaptation with Self-Supervised Embedding Optimization for Few-Shot Remote Sensing Scene Classification

The performance of deep learning is heavily influenced by the size of the learning samples, whose labeling process is time consuming and laborious. Deep learning algorithms typically assume that the training and prediction data are independent and uniformly distributed, which is rarely the case give...

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Bibliographic Details
Main Authors: Yong Li, Zhenfeng Shao, Xiao Huang, Bowen Cai, Song Peng
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
meta-learning
few-shot learning
remote sensing scene classification
self-supervised
transfer learning
Online Access:https://www.mdpi.com/2072-4292/13/14/2776

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https://www.mdpi.com/2072-4292/13/14/2776

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