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Efficient YOLO-based models for real-time ceramic crack detection
IAES International Journal of Artificial Intelligence · Vol. 15 No. 1 (2026) · hlm. 852–860
- ISSN
- 2252-8938, 2089-4872
- Terbit
- 2026-02-01
- Penerbit
- Institute of Advanced Engineering and Science
- Bahasa
- eng
Abstrak
The following research work systematically compares four variants of you only look once (YOLO), namely, YOLOv8, YOLOv9, YOLOv10, and YOLOv11 proposed recently, considering the key properties required to perform ceramic surface crack detection tasks with high computational efficiency, real-time inference speed, and low memory usage. A total of 300 images of ceramic surfaces were collected with manually labeled cracks and divided into training, validation, and testing sets in portions of 263, 22, and 15 images, respectively. Each of the four YOLO variants was trained for 50 and 100 epochs, and each was evaluated regarding mean average precision (mAP), inference time, model size, and computational complexity in giga floating point operations per second (GFLOPs). YOLOv9 produced the highest accuracy with mAP values as high as 0.752-0.79 but the highest cost in terms of increased computational complexity. However, among these methods, YOLOv8 can produce the fastest inference (~2-2.3 ms) with a small memory footprint (~6 MB) with an acceptable accuracy of ~0.65-0.67. The results showed that YOLOv8 is the most feasible to deploy in resource constrained industrial automation environments. By offering this comparative study, the research attempts to provide hints for the selection of appropriate YOLO-based models by practitioners in quality control applications related to ceramic manufacturing.
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19 penulis · 46 tautan kepenulisan bersama · 24 lintas organisasi
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- Rajamangala University of Technology
- Institut Teknologi Sepuluh Nopember
- Phranakhon Rajabhat University
- Institut Teknologi Dan Bisnis STIKOM Bali
- Sanata Dharma University
- University of Newcastle Australia
- Guizhou University of Engineering Science
- Organisasi lain
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Tampilkan sebagai tabel
| Rekan penulis | Organisasi | Artikel bersama |
|---|---|---|
| Yamin Thwe | Rajamangala University of Technology | 5 |
| Evi Triandini | Institut Teknologi Dan Bisnis STIKOM Bali | 4 |
| Elang Parikesit | Rajamangala University of Technology | 2 |
| I Komang Agus Ady Aryanto | Rajamangala University of Technology | 2 |
| Yuri Pamungkas | Institut Teknologi Sepuluh Nopember | 2 |
| Petrus Sutyasadi | Sanata Dharma University | 1 |
| Nipat Jongsawat | Rajamangala University of Technology | 1 |
| Anucha Tungkasthan | Rajamangala University of Technology | 1 |
| Ratri Dwi Indriani | Afiliasi tidak diketahui | 1 |
| Yuri Pamungkas | Afiliasi tidak diketahui | 1 |
| Stralen Pratasik | Institut Teknologi Sepuluh Nopember | 1 |
| Made Krisnanda | University of Newcastle Australia | 1 |
| Gao Yulan | Guizhou University of Engineering Science | 1 |
| Myo Min Aung | Rajamangala University of Technology | 1 |
| Abdul Karim | Hallym University | 1 |
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