A Joint Bayesian Optimization for the Classification of Fine Spatial Resolution Remotely Sensed Imagery Using Object-Based Convolutional Neural Networks

A Joint Bayesian Optimization for the Classification of Fine Spatial Resolution Remotely Sensed Imagery Using Object-Based Convolutional Neural Networks

In recent years, deep learning-based image classification has become widespread, especially in remote sensing applications, due to its automatic and strong feature extraction capability. However, as deep learning methods operate on rectangular-shaped image patches, they cannot accurately extract obj...

Full description

Bibliographic Details
Main Authors: Omer Saud Azeez, Helmi Z. M. Shafri, Aidi Hizami Alias, Nuzul Azam Haron
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Land
Subjects:
object-based convolution neural networks
deep learning
Bayesian optimization
decision-level fusion
Worldview-3
Online Access:https://www.mdpi.com/2073-445X/11/11/1905

Internet

https://www.mdpi.com/2073-445X/11/11/1905

Similar Items