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Authors: Christoph Brosch ; Alexander Bouwens ; Sebastian Bast ; Swen Haab and Rolf Krieger

Affiliation: Institut für Softwaresysteme, Hochschule Trier, Standort Birkenfeld, 55768 Hoppstädten-Weiersbach, Germany

Keyword(s): Machine Learning, Computer Vision, Product Image Dataset, Retail.

Abstract: The enormous progress in the field of artificial intelligence (AI) enables retail companies to automate their processes and thus to save costs. Thereby, many AI-based automation approaches are based on machine learning and computer vision. The realization of such approaches requires high-quality training data. In this paper, we describe the creation process of an annotated dataset that contains 1,034 images of single food products, taken under studio conditions, annotated with 5 class labels and 30 object detection labels, which can be used for product recognition and classification tasks. We based all images and labels on standards presented by GS1, a global non-profit organisation. The objective of our work is to support the development of machine learning models in the retail domain and to provide a reference process for creating the necessary training data.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Brosch, C.; Bouwens, A.; Bast, S.; Haab, S. and Krieger, R. (2023). Creation and Evaluation of a Food Product Image Dataset for Product Property Extraction. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-664-4; ISSN 2184-285X, SciTePress, pages 488-495. DOI: 10.5220/0012132400003541

@conference{data23,
author={Christoph Brosch. and Alexander Bouwens. and Sebastian Bast. and Swen Haab. and Rolf Krieger.},
title={Creation and Evaluation of a Food Product Image Dataset for Product Property Extraction},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - DATA},
year={2023},
pages={488-495},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012132400003541},
isbn={978-989-758-664-4},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - DATA
TI - Creation and Evaluation of a Food Product Image Dataset for Product Property Extraction
SN - 978-989-758-664-4
IS - 2184-285X
AU - Brosch, C.
AU - Bouwens, A.
AU - Bast, S.
AU - Haab, S.
AU - Krieger, R.
PY - 2023
SP - 488
EP - 495
DO - 10.5220/0012132400003541
PB - SciTePress

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