Analysis detection of real-time metallic surface defect using MobileNetV2 and YOLOv3 on Raspberry Pi
This work presents an innovative solution utilizing a Raspberry Pi detection system to identify any defects on metallic surfaces in real-time. Manual inspection has several limitations, including time-consuming, subjective assessments, and a higher probability of human error could compromise product...
| Main Authors: | Muhammad, Muhamad Sufri, Zainudin, Muhammad Noorazlan Shah, Idris, Muhammad Idzdihar, Kang, Soh Jun, Chee, Tan An, Xian, Teoh Yu, Alsayaydeh, Jamil Abedalrahim Jamil, Razali, Md Saifullah |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Semarak Ilmu Publishing
2024
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/119095/ http://psasir.upm.edu.my/id/eprint/119095/1/119095.pdf |
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