A review of Convolutional Neural Networks in Remote Sensing Image

Liu, Xinni and Han, Fengrong and Kamarul Hawari, Ghazali and Izzeldin, I. Mohd and Zhao, Yue (2019) A review of Convolutional Neural Networks in Remote Sensing Image. In: ICSCA '19: Proceedings of the 2019 8th International Conference on Software and Computer Applications , 19-22 February 2019 , Penang, Malaysia. pp. 263-267.. ISBN 978-1-4503-6573-4

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Effectively analysis of remote-sensing images is very important in many practical applications, such as urban planning, geospatial object detection, military monitoring, vegetation mapping and precision agriculture. Recently, convolutional neural network based deep learning algorithm has achieved a series of breakthrough research results in the fields of objective detection, image semantic segmentation and image classification, etc. Their powerful feature learning capabilities have attracted more attention and have important research value. In this article, firstly we have summarized the basic structure and several classical convolutional neural network architectures. Secondly, the recent research problems on convolutional neural network are discussed. Later, we summarized the latest research results in convolutional neural network based remote sensing fields. Finally, the conclusion has made on the basis of current issue on convolutional neural networks and the future development direction.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Convolutional neural network; deep learning; remote-sensing images
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Noorul Farina Arifin
Date Deposited: 13 Jan 2020 03:12
Last Modified: 13 Jan 2020 03:12
URI: http://umpir.ump.edu.my/id/eprint/27355
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