Orthogonal Capsule Network with Meta-Reinforcement Learning for Small Sample Hyperspectral Image Classification

Orthogonal Capsule Network with Meta-Reinforcement Learning for Small Sample Hyperspectral Image Classification

Most current hyperspectral image classification (HSIC) models require a large number of training samples, and when the sample size is small, the classification performance decreases. To address this issue, we propose an innovative model that combines an orthogonal capsule network with meta-reinforce...

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Bibliographic Details
Main Authors: Prince Yaw Owusu Amoako, Guo Cao, Boshan Shi, Di Yang, Benedict Boakye Acka
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Remote Sensing
Subjects:
hyperspectral image
capsule network
orthogonal layer
small sample classification
Online Access:https://www.mdpi.com/2072-4292/17/2/215
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