TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
SHOMY: Detection of Small Hazardous Objects using the You Only Look Once Algorithm |
| 영문제목(English Title) |
SHOMY: Detection of Small Hazardous Objects using the You Only Look Once Algorithm |
| 저자(Author) |
Eunchan Kim
Jinyoung Lee
Hyunjik Jo
Kwangtek Na
Eunsook Moon
Gahgene Gweon
Byungjoon Yoo
Yeunwoong Kyung
|
| 원문수록처(Citation) |
VOL 16 NO. 8 PP. 2688 ~ 2703 (2022. 8) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Research on the advanced detection of harmful objects in airport cargo for passenger safety against terrorism has increased recently. However, because associated studies are primarily focused on the detection of relatively large objects, research on the detection of small objects is lacking, and the detection performance for small objects has remained considerably low. Here, we verified the limitations of existing research on object detection and developed a new model called the Small Hazardous Object detection enhanced and reconstructed Model based on the You Only Look Once version 5 (YOLOv5) algorithm to overcome these limitations. We also examined the performance of the proposed model through different experiments based on YOLOv5, a recently launched object detection model. The detection performance of our model was found to be enhanced by 0.3 in terms of the mean average precision (mAP) index and 1.1 in terms of mAP (.5:.95) with respect to the YOLOv5 model. The proposed model is especially useful for the detection of small objects of different types in overlapping environments where objects of different sizes are densely packed. The contributions of the study are reconstructed layers for the Small Hazardous Object detection enhanced and reconstructed Model based on YOLOv5 and the non-requirement of data preprocessing for immediate industrial application without any performance degradation. |
| 키워드(Keyword) |
Computer vision
detection of hazardous items
small-object detection
YOLO
air transport
security industries
|
| 파일첨부 |
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