Transfer Learning applied to a Classification Task: a Case Study in the Footwear Industry



Convolutional Neural Networks, Image Classification, Transfer Learning, VGG16.


Convolutional Neural Networks are a widely used method for image classification. They are part of the Deep Learning area, whose main advantage is the fact that they do not require an human support to extract features from the images. In the context of the footwear industry, they represent a useful computational resource, being applied for style classification problems, machine vision, among others. This article aims to evaluate the performance of transfer learning methods for the purpose of hierarchical classification of new items of footwear products. For this purpose, a dataset composed by 5,177 images of women’s shoes was built. A pretrained architecture was selected to be refined, in order to produce a classification model. As a main result of this study, we confirm that the use of transfer learning speeds up deep neural nets training, allowing outstanding results through a VGG16 architecture. In terms of accuracy, the results achieved 99.97% and 98.42% for classifying respectively footwear categories and subcategories.


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Author Biographies

Fernando Gabriel Bloedorn, Universidade de Caxias do Sul, Brazil.

Graduated in Information Systems from Feevale University,Postgraduate in IT Administration from the University of Vale do Rio do Sinos and Postgraduate in Data Science from the University of Caxias do Sul. He serves as a Software Architect, Software Developer, Technical Lead and Information Technology Consultant. Enthusiast in the field of Data Science, Machine Learning and Artificial Intelligence.

Carine Geltrudes Webber, Universidade de Caxias do Sul, Brazil.

PhD in Computer Science from Ecole Doctorale Mathematiques et Informatiques, Universite de Grenoble I Joseph Fourier, France, Master (UFRGS) and Graduate (UCS) in Computer Science. She works as a Professor in the Exact Sciences and Engineering Knowledge Area at UCS. It integrates the Graduate Program in Teaching Science and Mathematics, developing the line of research on AI applied to Teaching. He works in several courses and research projects in the areas of Data Science and Industry 4.0.


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How to Cite

Bloedorn, F. G., & Webber, C. G. (2023). Transfer Learning applied to a Classification Task: a Case Study in the Footwear Industry. IEEE Latin America Transactions, 21(3), 427–433. Retrieved from