Three-dimensional Softmax mechanism guided bidirectional GRU networks for hyperspectral remote sensing image classification
Hyperspectral data is a valuable source of both spectral and spatial information. However, to enhance the classification accuracy of hyperspectral image features, it is crucial to capture the spatial spectral features of image elements. The recent years have witnessed the potentials of deep learning...
Saved in:
Main Authors: | Wu, Guoqiang, Ning, Xin, Hou, Luyang, He, Feng, Zhang, Hengmin, Shankar, Achyut |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/172195 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Superpixel guided deep-sparse-representation learning for hyperspectral image classification
by: Fan, Jiayuan, et al.
Published: (2020) -
Hyperspectral image classification by using pixel spatial correlation
by: Gao, Y., et al.
Published: (2014) -
Hyperspectral vision beyond 3D: a review
by: Antony, Maria Merin, et al.
Published: (2024) -
Hyperspectral reconstruction of SOTA method on natural image and remote sensing datasets
by: Zhou, Junzhe
Published: (2024) -
Deep ring-block-wise network for hyperspectral image classification
by: Xing, Changda, et al.
Published: (2023)