Application of Mask R-CNN and YOLOv8 algorithms for defect detection in printed circuit board manufacturing
Abstract In the last decades, machine vision and Machine Learning (ML) techniques have seen significant improvements in developing new algorithms thanks to the increment of hardware performance. Exploiting machine vision for specific technological applications became an essential opportunity to intr...
Saved in:
| Main Authors: | Maurizio Calabrese, Leonardo Agnusdei, Gianmauro Fontana, Gabriele Papadia, Antonio Del Prete |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-03-01
|
| Series: | Discover Applied Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s42452-025-06641-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Application of the mineral processing methods in recycling the waste printed circuit boards
by: Magdalinović Srđana, et al.
Published: (2024-01-01) -
YOLOv5-MDS: Target Detection Model for PCB Defect Inspection Based on YOLOv5 Integrated With Mamba Architecture
by: Deming Guo, et al.
Published: (2025-01-01) -
Identification of short circuits in electronic boards using electrical impedance spectroscopy
by: Yves Santos Borges, et al.
Published: (2025-03-01) -
TECHNOLOGY FOR CREATING THE TOPOLOGY OF PRINTED CIRCUIT BOARDS USING POLYMER 3D MASKS
by: Igor Nevliudov, et al.
Published: (2021-03-01) -
Pelarutan Selektif Tembaga dari Limbah Printed Circuit Board dengan Hidrogen Peroksida
by: Gatut Ari Wardani, et al.
Published: (2018-02-01)