Home / Research Library / YOLO-v1 to YOLO-v8, the Rise of YOLO and Its Compl...
🤖 Artificial Intelligence OpenAlex

YOLO-v1 to YOLO-v8, the Rise of YOLO and Its Complementary Nature toward Digital Manufacturing and Industrial Defect Detection

📅 June 23, 2023 👤 Muhammad Hussain 📖 Machines 📊 1,091 citations

🤖 Plain-English Summary

Since its inception in 2015, the YOLO (You Only Look Once) variant of object detectors has rapidly grown, with the latest release of YOLO-v8 in January 2023. This paper is the first to provide an in-depth review of the YOLO evolution from the original YOLO to the recent release (YOLO-v8) from the perspective of industrial manufacturing.

🔑 Key Findings

  • YOLO variants are underpinned by the principle of real-time and high-classification performance, based on limited but efficient computational parameters.
  • This principle has been found within the DNA of all YOLO variants with increasing intensity, as the variants evolve addressing the requirements of automated quality inspection within the industrial surface defect detection domain, such as the need for fast detection, high accuracy, and deployment onto constrained edge devices.
  • This paper is the first to provide an in-depth review of the YOLO evolution from the original YOLO to the recent release (YOLO-v8) from the perspective of industrial manufacturing.

💡 Why This Matters

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

Read the full paper
Access the original peer-reviewed research via OpenAlex.

View on DOI ↗

📋 Article Details

Category 🤖 Artificial Intelligence
Published Jun 23, 2023
Journal Machines
Authors Muhammad Hussain
DOI 10.3390/machines11070677
Citations 1,091
Source OpenAlex

More 🤖 Artificial Intelligence Research