3 papers
cs.CV2025
AutoDetect: Designing an Autoencoder-based Detection Method for Poisoning Attacks on Object Detection Applications in the Military Domain
Alma M. Liezenga, Stefan Wijnja, Puck de Haan +4
Poisoning attacks pose an increasing threat to the security and robustness of Artificial Intelligence systems in the military domain. The widespread use of open-source datasets and…
cs.CV2025
Occlusion Robustness of CLIP for Military Vehicle Classification
Jan Erik van Woerden, Gertjan Burghouts, Lotte Nijskens +4
Vision-language models (VLMs) like CLIP enable zero-shot classification by aligning images and text in a shared embedding space, offering advantages for defense applications with s…
cs.CV2024
Improving Object Detector Training on Synthetic Data by Starting With a Strong Baseline Methodology
Frank A. Ruis, Alma M. Liezenga, Friso G. Heslinga +6
Collecting and annotating real-world data for the development of object detection models is a time-consuming and expensive process. In the military domain in particular, data colle…