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Training a Computer Vision Model for Commercial Bakeries with Primarily Synthetic Images

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2024

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Gesellschaft für Informatik e.V.

Zusammenfassung

In the food industry, reprocessing returned products is a vital step to increase resource efficiency. [SBB23] presented an AI application that automates the tracking of returned bread buns. We extend their work by creating an expanded dataset comprising 2432 images and a wider range of baked goods. To increase model robustness, we use generative models pix2pix and CycleGAN to create synthetic images. We train state-of-the-art object detection models YOLOv9 and YOLOv8 on our detection task. Our overall best-performing model achieved an average precision AP 0.5 of 90.3% on our test set.

Beschreibung

Schmitt, Thomas H.; Bundscherer, Maximilian; Bocklet, Tobias (2024): Training a Computer Vision Model for Commercial Bakeries with Primarily Synthetic Images. INFORMATIK 2024. DOI: 10.18420/inf2024_150. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-746-3. pp. 1731-1740. Künstliche Intelligenz im Mittelstand / KI-KMU2024. Wiesbaden. 24.-26. September 2024

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