Efficient remote sensing image classification using the novel STConvNeXt convolutional network
Abstract Remote sensing images present formidable classification challenges due to their complex spatial organization, high inter-class similarity, and significant intra-class variability. To address the balance between computational efficiency and feature extraction capability in existing methods,...
Saved in:
| Main Authors: | Bo Liu, Chenmei Zhan, Cheng Guo, Xiaobo Liu, Shufen Ruan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-92629-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
ESSegNeXt: A Novel Building Extraction Framework Based on Generalized SamGeo and SegNeXt Models Using High-Resolution Remote Sensing Images
by: Qi Lu, et al.
Published: (2025-01-01) -
SegNeXt-RCMSCA: An improved SegNeXt network for detecting winter wheat lodging from UAS RGB images
by: Yahui Guo, et al.
Published: (2025-12-01) -
ACLC-Detection: A Network for Remote Sensing Image Detection Based on Attention Mechanism and Lightweight Convolution
by: Shaodong Liu, et al.
Published: (2025-07-01) -
LO-MLPRNN: A Classification Algorithm for Multispectral Remote Sensing Images by Fusing Selective Convolution
by: Xiangsuo Fan, et al.
Published: (2025-04-01) -
Alzheimer’s disease diagnosis by 3D-SEConvNeXt
by: Zhongyi Hu, et al.
Published: (2025-01-01)