Remote sensing image description based on word embedding and end-to-end deep learning
Abstract This study proposes an end-to-end image description generation model based on word embedding technology to realise the classification and identification of Populus euphratica and Tamarix in complex remote sensing images by providing descriptions in precise and concise natural sentences. Fir...
Guardado en:
Autores principales: | Yuan Wang, Hongbing Ma, Kuerban Alifu, Yalong Lv |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/a4f7d8083d4d486fa8fce75c5f6fc3bf |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
End-to-End SAR Deep Learning Imaging Method Based on Sparse Optimization
por: Siyuan Zhao, et al.
Publicado: (2021) -
Natural language word embeddings as a glimpse into healthcare language and associated mortality surrounding end of life
por: Wei Gao, et al.
Publicado: (2021) -
Dual Head and Dual Attention in Deep Learning for End-to-End EEG Motor Imagery Classification
por: Meiyan Xu, et al.
Publicado: (2021) -
End-to-End Deep Learning by MCU Implementation: Indoor Localization by Sound Spectrum of Light Fingerprints
por: Chung-Wen Hung, et al.
Publicado: (2021) -
Deep learning for end-to-end kidney cancer diagnosis on multi-phase abdominal computed tomography
por: Kwang-Hyun Uhm, et al.
Publicado: (2021)