Towards Small Anomaly Detection

Thomas Messerer

2024

Abstract

In this position paper, we describe the design of a camera-based FOD (Foreign Object Debris) detection system intended for use in the parking position at the airport. FOD detection, especially the detection of small objects, requires a great deal of human attention. The transfer of ML (machine learning) from the laboratory to the field calls for adjustments, especially in testing the model. Automated detection requires not only high detection performance and low false alarm rate, but also good generalization to unknown objects. There is not much data available for this use case, so in addition to ML methods, the creation of training and test data is also considered.

Paper Citation

in Harvard Style

Messerer T. (2024). Towards Small Anomaly Detection. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-684-2, SciTePress, pages 860-865. DOI: 10.5220/0012459800003654

in Bibtex Style

@conference{icpram24,
author={Thomas Messerer},
title={Towards Small Anomaly Detection},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2024},
pages={860-865},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012459800003654},
isbn={978-989-758-684-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Towards Small Anomaly Detection
SN - 978-989-758-684-2
AU - Messerer T.
PY - 2024
SP - 860
EP - 865
DO - 10.5220/0012459800003654
PB - SciTePress