VoltaVision: A Transfer Learning model for electronic component classification

• URL: http://arxiv.org/abs/2404.03898v1
• Date: Fri, 5 Apr 2024 05:42:23 GMT
• Title: VoltaVision: A Transfer Learning model for electronic component classification
• Authors: Anas Mohammad Ishfaqul Muktadir Osmani, Taimur Rahman, Salekul Islam,
• Abstract summary: We introduce a lightweight CNN, coined as VoltaVision, and compare 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.
• Score: 1.4132765964347058
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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