A deep relearning method based on the recurrent neural network for land cover classification

A deep relearning method based on the recurrent neural network for land cover classification

Recent developments in deep learning (DL) techniques have provided a series of new methods for land cover classification. However, most DL-based methods do not consider the rich spatial association of land cover classes embedded in remote sensing images. In this research, a deep relearning method ba...

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Bibliographic Details
Main Authors: Yunwei Tang, Fang Qiu, Bangjin Wang, Di Wu, Linhai Jing, Zhongchang Sun
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:GIScience & Remote Sensing
Subjects:
recurrent neural networks (rnn)
relearning
gated recurrent unit (gru)
long short-term memory (lstm)
land cover classification
Online Access:http://dx.doi.org/10.1080/15481603.2022.2115589

Internet

http://dx.doi.org/10.1080/15481603.2022.2115589

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