A Hybrid 3D–2D Feature Hierarchy CNN with Focal Loss for Hyperspectral Image Classification

A Hybrid 3D–2D Feature Hierarchy CNN with Focal Loss for Hyperspectral Image Classification

Hyperspectral image (HSI) classification has been extensively applied for analyzing remotely sensed images. HSI data consist of multiple bands that provide abundant spatial information. Convolutional neural networks (CNNs) have emerged as powerful deep learning methods for processing visual data. In...

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Bibliographic Details
Main Authors: Xiaoyan Wen, Xiaodong Yu, Yufan Wang, Cuiping Yang, Yu Sun
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Remote Sensing
Subjects:
hyperspectral remote sensing images
feature extraction
convolutional neural network (CNN)
class imbalance
focal loss
Online Access:https://www.mdpi.com/2072-4292/15/18/4439

Internet

https://www.mdpi.com/2072-4292/15/18/4439

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