Rock Identification Method based on YOLOv8

Authors

  • Yaozhen Li
  • Ziji Wang
  • Xinyi Zheng
  • Yixin Zhao
  • Yuan Chang

DOI:

https://doi.org/10.6919/ICJE.202408_10(8).0016

Keywords:

YOLOv8; Rock Recognition; Deep Learning; Object Detection; Geological Exploration.

Abstract

The traditional rock identification methods mainly rely on the field survey and laboratory analysis of geologists. These methods are not only time-consuming and labor-intensive, but also limited by the experience and subjective judgment of geologists. With the rapid development of computer vision and deep learning technology, especially the continuous progress of target detection algorithm, automatic rock recognition technology based on image processing has gradually become a research hotspot. In this paper, a rock recognition system based on YOLOv8 is proposed. The system utilizes the efficiency and accuracy of YOLOv8 algorithm to realize the fast and accurate recognition of various rock types. By constructing a rock image dataset, training a deep learning model, and testing it in a real scene, the system achieves satisfactory recognition results. The research in this paper is of great significance for improving the efficiency and accuracy of rock identification and promoting geological exploration and resource development.

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References

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Published

2024-07-22

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Section

Articles

How to Cite

Li, Yaozhen, Ziji Wang, Xinyi Zheng, Yixin Zhao, and Yuan Chang. 2024. “Rock Identification Method Based on YOLOv8”. International Core Journal of Engineering 10 (8): 113-21. https://doi.org/10.6919/ICJE.202408_10(8).0016.