A Review of Yolo Algorithm Developments

A Review of Yolo Algorithm Developments. Jiang, P., Ergu, D., Liu, F., Cai, Y., & Ma, B. Procedia Computer Science, 199:1066-1073, Elsevier, 1, 2022.

Paper doi abstract bibtex

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.

@article{
 title = {A Review of Yolo Algorithm Developments},
 type = {article},
 year = {2022},
 keywords = {Object detection,Public data analysis,Review,Yolo},
 pages = {1066-1073},
 volume = {199},
 month = {1},
 publisher = {Elsevier},
 day = {1},
 id = {a19843d7-8369-3328-b2f5-9cfd37e1458a},
 created = {2024-03-16T12:58:17.064Z},
 accessed = {2024-03-16},
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 last_modified = {2024-03-16T12:58:19.655Z},
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 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.},
 bibtype = {article},
 author = {Jiang, Peiyuan and Ergu, Daji and Liu, Fangyao and Cai, Ying and Ma, Bo},
 doi = {10.1016/J.PROCS.2022.01.135},
 journal = {Procedia Computer Science}
}

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