Abstract
Application of neural networks in industrial settings, such as automated factories with bin-picking solutions requires costly production of large labeled datasets. This paper presents an automatic data generation tool with a procedural model of a cardboard box. We briefly demonstrate the capabilities of the system, and its various parameters and empirically prove the usefulness of the generated synthetic data by training a simple neural network. We make sample synthetic data generated by the tool publicly available.
Supported by the TERAIS project in the framework of the program Horizon-Widera-2021 of the European Union under the Grant agreement number 101079338.
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Kravár, P., Gajdoech, L., Madaras, M. (2023). Novel Synthetic Data Tool for Data-Driven Cardboard Box Localization. In: Iliadis, L., Papaleonidas, A., Angelov, P., Jayne, C. (eds) Artificial Neural Networks and Machine Learning – ICANN 2023. ICANN 2023. Lecture Notes in Computer Science, vol 14254. Springer, Cham. https://doi.org/10.1007/978-3-031-44207-0_50
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DOI: https://doi.org/10.1007/978-3-031-44207-0_50
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