Fully Convolutional Neural Network with Augmented Atrous Spatial Pyramid Pool and Fully Connected Fusion Path for High Resolution Remote Sensing Image Segmentation

Fully Convolutional Neural Network with Augmented Atrous Spatial Pyramid Pool and Fully Connected Fusion Path for High Resolution Remote Sensing Image Segmentation

Recent developments in Convolutional Neural Networks (CNNs) have allowed for the achievement of solid advances in semantic segmentation of high-resolution remote sensing (HRRS) images. Nevertheless, the problems of poor classification of small objects and unclear boundaries caused by the characteris...

Full description

Bibliographic Details
Main Authors: Guangsheng Chen, Chao Li, Wei Wei, Weipeng Jing, Marcin Woźniak, Tomas Blažauskas, Robertas Damaševičius
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Applied Sciences
Subjects:
semantic segmentation
remote sensing
dilated convolution
fully convolutional neural network
deep learning
Online Access:https://www.mdpi.com/2076-3417/9/9/1816

Internet

https://www.mdpi.com/2076-3417/9/9/1816

Similar Items