Abstract
Object detection techniques are the foundation for the artificial intelligence field. This research paper gives a brief overview of the You Only Look Once (YOLO) algorithm and its subsequent advanced versions. Through the analysis, we reach many remarks and insightful results. The results show the differences and similarities among the YOLO versions and between YOLO and Convolutional Neural Networks (CNNs). The central insight is the YOLO algorithm improvement is still ongoing.This article briefly describes the development process of the YOLO algorithm, summarizes the methods of target recognition and feature selection, and provides literature support for the targeted picture news and feature extraction in the financial and other fields. Besides, this paper contributes a lot to YOLO and other object detection literature.
Original language | English |
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Pages (from-to) | 1066-1073 |
Number of pages | 8 |
Journal | Procedia Computer Science |
Volume | 199 |
DOIs | |
Publication status | Published - 2021 |
Externally published | Yes |
Event | 8th International Conference on Information Technology and Quantitative Management, ITQM 2020 and 2021 - Chengdu, China Duration: 9 Jul 2021 → 11 Jul 2021 |
Keywords
- Object detection
- Public data analysis
- Review
- Yolo