Review of CNN in aerial image processing
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 im...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English English |
| Published: |
Taylor and Francis Ltd.
2023
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/41822/1/Review%20of%20CNN%20in%20aerial%20image%20processing.pdf http://umpir.ump.edu.my/id/eprint/41822/2/Review%20of%20CNN%20in%20aerial%20image%20processing_ABS.pdf http://umpir.ump.edu.my/id/eprint/41822/ https://doi.org/10.1080/13682199.2023.2174651 https://doi.org/10.1080/13682199.2023.2174651 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|