A Machine Learning Approach to Approximate the Age of a Digital Image. - Robert Jöchl; Andreas Uhl (IWDW, 2020)

Assessment of Sensor Ageing-Impact in Air Travelled Fingerprint Capturing Devices. - Christof Kauba; Simon Kirchgasser; Robert Jöchl; Andreas Uhl (BIOSIG, 2021)

Identification Of In-Field Sensor Defects In The Context Of Image Age Approximation. - Robert Jöchl; Andreas Uhl (ICIP, 2021)

Effects of Image Compression on Image Age Approximation. - Robert Jöchl; Andreas Uhl (IWDW, 2021)

Apart from In-field Sensor Defects, are there Additional Age Traces Hidden in a Digital Image? - Robert Jöchl; Andreas Uhl (WIFS, 2021)

Can point-cloud based neural networks learn fingerprint variability? - Dominik Söllinger; Robert Jöchl; Simon Kirchgasser; Andreas Uhl (BIOSIG, 2022)

Deep Learning Image Age Approximation - What is More Relevant: Image Content or Age Information? - Robert Jöchl; Andreas Uhl (IWDW, 2022)

Content Bias in Deep Learning Age Approximation: A new Approach Towards more Explainability. - Robert Jöchl; Andreas Uhl (CoRR, 2023)

PLUS Temporal Image Forensics Dataset. - Robert Jöchl; Andreas Uhl (WIFS, 2024)

Device (In)Dependence of Deep Learning-based Image Age Approximation. - Robert Jöchl; Andreas Uhl (CoRR, 2024)

Content bias in deep learning image age approximation: A new approach towards better explainability. - Robert Jöchl; Andreas Uhl (Pattern Recognit. Lett., 2024)

FaceQSORT: Can a Combination of two Biometric Features Achieve Competitive Performance? - Robert Jöchl; Andreas Uhl (DSP, 2025)

FaceQSORT: a Multi-Face Tracking Method based on Biometric and Appearance Features. - Robert Jöchl; Andreas Uhl (CoRR, 2025)