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A Review of Yolo Algorithm Developments

📅 Published: January 1, 2022 👤 Peiyuan Jiang, Daji Ergu, Fangyao Liu et al. 📖 Procedia Computer Science 📊 2,562 citations
AI-Generated Summary

Object detection techniques are the foundation for the artificial intelligence field. 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.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 This research paper gives a brief overview of the You Only Look Once (YOLO) algorithm and its subsequent advanced versions.
  • 2 Through the analysis, we reach many remarks and insightful results.
  • 3 The results show the differences and similarities among the YOLO versions and between YOLO and Convolutional Neural Networks (CNNs).
Why It Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

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Article Details
Source OpenAlex
Category 🤖 Artificial Intelligence
Published Jan 1, 2022
Journal Procedia Computer Science
DOI 10.1016/j.procs.2022.01.135
Citations 2,562
Authors Peiyuan Jiang, Daji Ergu, Fangyao Liu, Ying Cai, Bo Ma