Deep learning techniques for image recognition of counterfeited luxury handbags materials

P. Apipawinwongsa; Y. Limpiyakorn

doi:10.1117/12.2644669

12 October 2022 Deep learning techniques for image recognition of counterfeited luxury handbags materials

P. Apipawinwongsa, Y. Limpiyakorn

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123420X (2022) https://doi.org/10.1117/12.2644669
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

Due to the fact that counterfeit in second-handed goods terribly affects trading in markets of second-handed luxury bags, users in this research thus present studies of methods to classify genuineness of ‘Gucci GG Canvas’ with the pretrained model from Model VGG16 and with DenseNet121 to design deep Convolutional Neural Networks (CNN) model for binary classification. The CNN together with DenseNet121 model comprises accuracy at 95%, which is more than the 2 prior models, i.e., CNN from scratch and CNN together with VGG16.

Citation Download Citation

P. Apipawinwongsa and Y. Limpiyakorn "Deep learning techniques for image recognition of counterfeited luxury handbags materials", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123420X (12 October 2022); https://doi.org/10.1117/12.2644669

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