Sequence-based object detection with yolov7
- 주제(키워드) Sequence-based detection , Object detection , YOLOv7
- 주제(DDC) 510
- 발행기관 아주대학교
- 지도교수 신동욱
- 발행년도 2023
- 학위수여년월 2023. 8
- 학위명 석사
- 학과 및 전공 일반대학원 수학과
- 실제URI http://www.dcollection.net/handler/ajou/000000033041
- 본문언어 영어
- 저작권 아주대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
In this paper, we propose a novel algorithm called sequence-based object detection to identify accidents in advance and prevent secondary accidents. To evaluate our proposed algorithm, we also propose a novel metric called sequence-based evaluation. We trained model for two datasets, one-class dataset and three-class dataset. For one-class dataset, we used focal loss, and as the results we achieved mAP@0.5 score above o.8 and accuracy 1.0. For three-class dataset, we compared focal loss and quality focal loss, and as the results we achieved mAP@0.5 score above 0.7 and accuracy 1.0.
more목차
1. Introduction 1
2. Related Works 2
2.1 YOLO 2
2.2 Loss function 2
3. Data 5
3.1 One-class dataset 5
3.2 Three-class dataset 6
4. Method 8
5. Experiments 10
5.1 One-Class Dataset 10
5.2 Three-Class Dataset 11
6. Conclusion 13
7. References 15
