Cargando…
Land Cover Classification of UAV Remote Sensing Based on Transformer–CNN Hybrid Architecture
High-precision land cover maps of remote sensing images based on an intelligent extraction method are an important research field for many scholars. In recent years, deep learning represented by convolutional neural networks has been introduced into the field of land cover remote sensing mapping. In...
Autores principales: | Lu, Tingyu, Wan, Luhe, Qi, Shaoqun, Gao, Meixiang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256031/ https://www.ncbi.nlm.nih.gov/pubmed/37300015 http://dx.doi.org/10.3390/s23115288 |
Ejemplares similares
-
HyFormer: Hybrid Transformer and CNN for Pixel-Level Multispectral Image Land Cover Classification
por: Yan, Chuan, et al.
Publicado: (2023) -
A novel hybrid transformer-CNN architecture for environmental microorganism classification
por: Shao, Ran, et al.
Publicado: (2022) -
Remote sensing based analysis of land cover and land cover change in Central Sulawesi, Indonesia
por: Knieper, Christian, et al.
Publicado: (2012) -
Scale Effect of Land Cover Classification from Multi-Resolution Satellite Remote Sensing Data
por: Li, Runxiang, et al.
Publicado: (2023) -
Remote Sensing Image Scene Classification in Hybrid Classical–Quantum Transferring CNN with Small Samples
por: Zhang, Zhouwei, et al.
Publicado: (2023)