Deep Feature Aggregation Network for Hyperspectral Remote Sensing Image Classification

Deep Feature Aggregation Network for Hyperspectral Remote Sensing Image Classification

Hyperspectral remote sensing images (HSIs) are rich in spectral-spatial information. The deep learning models can help to automatically extract and discover this rich information from HSIs for classifying HSIs. However, the sampling of the models and the design of the hyperparameters depend on the n...

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Bibliographic Details
Main Authors: Chunju Zhang, Guandong Li, Runmin Lei, Shihong Du, Xueying Zhang, Hui Zheng, Zhaofu Wu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Dense connectivity
feature fusion
hyperspectral image classification
residual learning
3-D convolutional neural network (3D-CNN)
Online Access:https://ieeexplore.ieee.org/document/9184224/

Internet

https://ieeexplore.ieee.org/document/9184224/

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