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Small Object Detection using Prediction head and Attention

Authors
Kim, Hae MoonKim, Ji HoonPark, Kyung RiMoon, Young Shik
Issue Date
Mar-2022
Publisher
IEEE
Keywords
object detection; small object detection; attention module
Citation
2022 International Conference on Electronics, Information, and Communication (ICEIC), pp 1 - 4
Pages
4
Indexed
SCIE
SCOPUS
Journal Title
2022 International Conference on Electronics, Information, and Communication (ICEIC)
Start Page
1
End Page
4
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/112538
DOI
10.1109/ICEIC54506.2022.9748393
Abstract
UAV(Unmanned aerial vehicle)-captured image contains a number of small object. Object captured in UAV's low altitude flight are expressed as low resolution in the image and have ambiguous boundaries. The detection problem of small objects expressed in limited pixels in UAV-captured images is difficult. In this paper, we used an additional prediction head to improve the detection performance o small objects, and modified the channel attention module of CBAM and added it to the PANet. The experiment showed that the proposed method showed a 4.1% improvement in| mAP performance compared to the existing method in VisDrone 2020-DET dataset
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