DeepTronic: An electronic device classification model using deep convolutional neural networks

• Main Authors: Salvador, Rodolfo C., Bandala, Argel A., Javel, Irister M., Bedruz, Rhen Anjerome R., Dadios, Elmer P., Vicerra, Ryan Rhay P.
• Format: text
• Published: Animo Repository 2019
• Subjects: Neural networks (Computer science); Transfer learning (Machine learning); Passive components—Classification; Reverse engineering; Manufacturing
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/3025
• Institution: De La Salle University

This paper presents a novel and straightforward way of classifying discrete and surface-mount electronic components found on electronic prototypes using transfer learning and deep convolutional neural networks (DCNN). The goal of this study is to precisely classify images of electronic components in...