VoltaVision: A Transfer Learning model for electronic component classification

Anas Mohammad Ishfaqul Muktadir Osmani, Taimur Rahman, Salekul Islam

Keywords: Electrical component recognition, Transfer Learning, Computer Vision, Deep Neural Network

TL;DR: We proposed a lightweight custom CNN model to classify three electronic components using transfer learning

Abstract: In this paper, we analyze the effectiveness of transfer learning on classifying electronic components. Transfer learning reuses pre-trained models to save time and resources in building a robust classifier rather than learning from scratch. Our work introduces a lightweight CNN, coined as VoltaVision, and compares its performance against more complex models. We test the hypothesis that transferring knowledge from a similar task to our target domain yields better results than state-of-the-art models trained on general datasets. Our dataset and code for this work are available at https://github.com/AnasIshfaque/VoltaVision.

Submission Number: 130