Annals of Computer Science and Information Systems, Volume 12

DOI: http://dx.doi.org/10.15439/2017F526

Citation: Position Papers of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 12, pages 3–9 (2017)

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Abstract. This paper deals with re-training neural network-based image classification model, using so-called Transfer Learning approach. This method allows for creating a new image classifier, reusing pre-trained weights from a publicly available model. Our study gives some insight on accuracy of re-trained models and provides guidelines concerning required number of training examples. Presented results may be useful for computer vision practitioners, who would like to adapt results of state-of-the-art research on neural networks for their own customized image recognition models.

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