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Research Paper
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Paper Title

EXPOSURE OF DEFECTED PCB USING PYTHON

Article Identifiers

Registration ID: IJNRD_192656

Published ID: IJNRD2304616

: http://doi.one/10.1729/Journal.33905

Keywords

- Convolution Neural Network, YOLO-v5, Deep Learning, Printed Circuit Board (PCB)

Abstract

Abstract : The importance of having a defect-free Printed Circuit Board (PCB) has increased in today's modern era due to the high demand for low-cost electronic items. Such systems require PCBs with no errors, making it crucial to detect defects and imperfections to create high-quality, error-free PCBs. To accomplish this, a defect detection system that uses images of the PCBs has been developed. The YOLO-v5 model is a new model that has been implemented to detect defects in PCBs. Many models and different approaches have been implemented in the past for the quality inspection of PCBs to detect defects. The YOLO models, including YOLO, YOLO-v2, YOLO-v3, YOLO-v4, and Tiny-YOLO-v2, are the state-of-the-art in the artificial intelligence industry. YOLO-v5 is a game changer for many industries such as the electronic industry as it provides excellent efficacy, precision, and speed. In this project, 1386 images with 6 different types of defects were used, and the YOLO-v5 algorithm was trained with a batch size of 16 and a trained epoch of 500. As a result, this model achieved a defect detection accuracy of over 90% mAP in PCBs

How To Cite (APA)

Ammati Santhi priya, Dr.S.Aruna, S.Keerthi Mahalakshmi, K.Supraja, & M.Rama satya sai and B. sai siva sri (April-2023). EXPOSURE OF DEFECTED PCB USING PYTHON. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), g109-g115. http://doi.one/10.1729/Journal.33905

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Other Publication Details

Paper Reg. ID: IJNRD_192656

Published Paper Id: IJNRD2304616

Downloads: 000122018

Research Area: Electronics & Communication Engg. 

Author Type: Indian Author

Country: VIJAYAWADA, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304616.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304616

Crossref DOI: http://doi.one/10.1729/Journal.33905

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