원문정보
한국차세대컴퓨팅학회
한국차세대컴퓨팅학회 학술대회
The 8th International Conference on Next Generation Computing 2022
2022.10
pp.205-206
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this paper, by cross-applying the DINO (DETR with Improved deNoising anchOrboxes) model to various datasets, we examine what characteristics of dataset are effective for traffic object detection training. DINO model is best DETR (DEtection with TRansformer)-like model in object detection. For the experiment, a total of two datasets were used: COCO and BDD100K datasets. As a result of evaluation with BDD100K dataset which contains diverse driving images, dataset with the same texture as the evaluation dataset showed similar performance with less data than the high texture dataset focused on each object.
목차
Abstract
I. INTRODUCTION
II. DATASET CROSS APPLICATION USING DINO MODEL
A. DINO model
B. Modify dataset
C. Experiments and Results
III. CONCLUSION
REFERENCES
I. INTRODUCTION
II. DATASET CROSS APPLICATION USING DINO MODEL
A. DINO model
B. Modify dataset
C. Experiments and Results
III. CONCLUSION
REFERENCES