Review of CNN in aerial image processing

被引:10
|
作者
Liu, Xinni [1 ]
Ghazali, Kamarul Hawari [2 ]
Han, Fengrong [3 ]
Mohamed, Izzeldin Ibrahim [2 ]
机构
[1] Xian Univ Finance & Econ, Xian, Peoples R China
[2] Univ Malaysia Pahang, Pekan, Malaysia
[3] Baoji Univ Arts & Sci, Baoji, Peoples R China
来源
IMAGING SCIENCE JOURNAL | 2023年 / 71卷 / 01期
关键词
Aerial image; review; image processing; drone technology; object detection; image classification; deep learning algorithm; convolutional neural networks; SEMANTIC SEGMENTATION; SCENE CLASSIFICATION; VEHICLE DETECTION; DEEP; NETWORK;
D O I
10.1080/13682199.2023.2174651
中图分类号
TB8 [摄影技术];
学科分类号
0804 ;
摘要
In recent years, deep learning algorithm has been used in many applications mainly in image processing of object detection and classification. The use of image processing techniques is becoming more interesting with the existence of drone technology with the employ of deep learning in aerial view image processing because of the high resolution and heaps of images taken. This paper aims to review neural networks specifically on the aerial view image by drones and to discuss the work principles and classic architectures of convolutional neural networks, its latest research trend and typical models along with target detection in object detection, image classification and semantic segmentation. In addition, this study also provided a specific application in the aerial image. Finally, the limitations of the convolutional network and expected future development trends were also discussed. Based on the findings, the deep learning algorithm was observed to provide high accuracy, it outperformed other generally image processing-based techniques.
引用
收藏
页码:1 / 13
页数:13
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