Combining Image and Text Matching for Product Classification in Retail$$^*$$

Author:

Bast Sebastian,Brosch Christoph,Krieger Rolf

Publisher

Springer Nature Switzerland

Reference27 articles.

1. Bast, S., Brosch, C., Krieger, R.: A hybrid approach for product classification based on image and text matching. In: Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA, pp. 293–300. SciTePress, Lisbon, Portugal (2022)

2. How Global Product Classification (GPC) works, GS1. https://www.gs1.org/standards/gpc/how-gpc-works. Accessed 20 Oct 2022

3. Karami, E., Prasad, S., Shehata, M.: Image matching using SIFT, SURF, BRIEF and ORB: performance comparison for distorted images. In: Proceedings of the 2015 Newfoundland Electrical and Computer Engineering Conference, St. Johns, Canada (2015)

4. LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521, 436–444 (2015)

5. Wei, Y., Tran, S., Xu, S., Kang, B., Springer, M.: Deep learning for retail product recognition: challenges and techniques. Comput. Intell. Neurosci. 2020, 1–23 (2020)

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