Cargando…
Convolutional Neural Network Based on Extreme Learning Machine for Maritime Ships Recognition in Infrared Images
The success of Deep Learning models, notably convolutional neural networks (CNNs), makes them the favorable solution for object recognition systems in both visible and infrared domains. However, the lack of training data in the case of maritime ships research leads to poor performance due to the pro...
Autores principales: | Khellal, Atmane, Ma, Hongbin, Fei, Qing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982679/ https://www.ncbi.nlm.nih.gov/pubmed/29747439 http://dx.doi.org/10.3390/s18051490 |
Ejemplares similares
-
Cerebral Microbleed Detection via Convolutional Neural Network and Extreme Learning Machine
por: Lu, Siyuan, et al.
Publicado: (2021) -
Recognition of industrial machine parts based on transfer learning with convolutional neural network
por: Li, Qiaoyang, et al.
Publicado: (2021) -
Multimodal medical image fusion using convolutional neural network and extreme learning machine
por: Kong, Weiwei, et al.
Publicado: (2022) -
Application of Convolutional Neural Network (CNN) to Recognize Ship Structures
por: Lim, Jae-Jun, et al.
Publicado: (2022) -
Assessment of global shipping risk caused by maritime piracy
por: He, Zhaoyang, et al.
Publicado: (2023)