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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...

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Uloženo v:
Hlavní autoři: Guangsheng Chen, Chao Li, Wei Wei, Weipeng Jing, Marcin Woźniak, Tomas Blažauskas, Robertas Damaševičius
Médium: Artigo
Jazyk:Inglês
Vydáno: MDPI AG 2019-05-01
Edice:Applied Sciences
Témata:
semantic segmentation
remote sensing
dilated convolution
fully convolutional neural network
deep learning
On-line přístup:https://www.mdpi.com/2076-3417/9/9/1816
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