A review of Convolutional Neural Networks in Remote Sensing Image
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...
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| Format: | Conference or Workshop Item |
| Language: | en |
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ACM Digital Library
2019
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| Online Access: | http://umpir.ump.edu.my/id/eprint/27355/1/A%20review%20of%20Convolutional%20Neural%20Networks1.pdf http://umpir.ump.edu.my/id/eprint/27355/ https://doi.org/10.1145/3316615.3316712 |
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| author | Liu, Xinni Han, Fengrong Kamarul Hawari, Ghazali Izzeldin, I. Mohd Zhao, Yue |
| author_facet | Liu, Xinni Han, Fengrong Kamarul Hawari, Ghazali Izzeldin, I. Mohd Zhao, Yue |
| author_sort | Liu, Xinni |
| building | UMPSA Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | 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. |
| format | Conference or Workshop Item |
| id | my.ump.umpir.27355 |
| institution | Universiti Malaysia Pahang |
| language | en |
| publishDate | 2019 |
| publisher | ACM Digital Library |
| record_format | eprints |
| spelling | my.ump.umpir.273552020-01-13T03:12:26Z http://umpir.ump.edu.my/id/eprint/27355/ A review of Convolutional Neural Networks in Remote Sensing Image Liu, Xinni Han, Fengrong Kamarul Hawari, Ghazali Izzeldin, I. Mohd Zhao, Yue QA75 Electronic computers. Computer science 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. ACM Digital Library 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/27355/1/A%20review%20of%20Convolutional%20Neural%20Networks1.pdf 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 (Published) https://doi.org/10.1145/3316615.3316712 |
| spellingShingle | QA75 Electronic computers. Computer science Liu, Xinni Han, Fengrong Kamarul Hawari, Ghazali Izzeldin, I. Mohd Zhao, Yue A review of Convolutional Neural Networks in Remote Sensing Image |
| title | A review of Convolutional Neural Networks in Remote Sensing Image |
| title_full | A review of Convolutional Neural Networks in Remote Sensing Image |
| title_fullStr | A review of Convolutional Neural Networks in Remote Sensing Image |
| title_full_unstemmed | A review of Convolutional Neural Networks in Remote Sensing Image |
| title_short | A review of Convolutional Neural Networks in Remote Sensing Image |
| title_sort | review of convolutional neural networks in remote sensing image |
| topic | QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/27355/1/A%20review%20of%20Convolutional%20Neural%20Networks1.pdf http://umpir.ump.edu.my/id/eprint/27355/ https://doi.org/10.1145/3316615.3316712 |
| url_provider | http://umpir.ump.edu.my/ |