Abstract
This paper investigates the classification of brand images using convolutional neural networks. Traditionally, the images must be manually named, classified, and tagged, which is a laborious and time-consuming task. Nowadays, these processes can be addressed with the help of computer vision for brand classification. An approach to create a Convolutional Neural Network (CNN) model with a high accuracy is proposed and discussed, in which the images in the classification process are automatically tagged with the predicted class name.
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Ruf, Y., Hanne, T., Dornberger, R. (2023). Classification of Brand Images Using Convolutional Neural Networks. In: Abraham, A., Hanne, T., Gandhi, N., Manghirmalani Mishra, P., Bajaj, A., Siarry, P. (eds) Proceedings of the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022). SoCPaR 2022. Lecture Notes in Networks and Systems, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-031-27524-1_50
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DOI: https://doi.org/10.1007/978-3-031-27524-1_50
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