A Novel 2D-3D CNN with Spectral-Spatial Multi-Scale Feature Fusion for Hyperspectral Image Classification
Multifarious hyperspectral image (HSI) classification methods based on convolutional neural networks (CNN) have been gradually proposed and achieve a promising classification performance. However, hyperspectral image classification still suffers from various challenges, including abundant redundant...
Enregistré dans:
Auteurs principaux: | Dongxu Liu, Guangliang Han, Peixun Liu, Hang Yang, Xinglong Sun, Qingqing Li, Jiajia Wu |
---|---|
Format: | article |
Langue: | EN |
Publié: |
MDPI AG
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/e34cd057da4b4e6ebba8d152865c16d3 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Hyperspectral Image Classification via a Novel Spectral–Spatial 3D ConvLSTM-CNN
par: Ghulam Farooque, et autres
Publié: (2021) -
Progressive Guided Fusion Network With Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection
par: Jiajia Wu, et autres
Publié: (2021) -
Deep Spectral Spatial Inverted Residual Network for Hyperspectral Image Classification
par: Tianyu Zhang, et autres
Publié: (2021) -
Hyperspectral Image Classification Based on Two-Branch Spectral–Spatial-Feature Attention Network
par: Hanjie Wu, et autres
Publié: (2021) -
Real-Time 2-D Lidar Odometry Based on ICP
par: Fuxing Li, et autres
Publié: (2021)