1 code implementation • 2 Feb 2023 • Franziska Schirrmacher, Benedikt Lorch, Anatol Maier, Christian Riess
Such an uncertainty measure allows to detect false predictions, indicating an analyst when not to trust the result of the automated license plate recognition.
no code implementations • 28 Sep 2022 • Andreas Spruck, Maximilane Gruber, Anatol Maier, Denise Moussa, Jürgen Seiler, Christian Riess, André Kaup
The benefits of the proposed data generation pipeline, especially for machine learning scenarios with limited available training data, are demonstrated by an extensive experimental validation in the context of automatic license plate recognition.
no code implementations • 27 Sep 2022 • Andreas Spruck, Maximiliane Hawesch, Anatol Maier, Christian Riess, Jürgen Seiler, André Kaup
Applying the proposed method, improvements of up to 2. 79 percentage points in terms of Character Error Rate (CER), and up to 7. 88 percentage points in terms of Word Error Rate (WER) are achieved on the subset.
no code implementations • 29 Jul 2022 • Denise Moussa, Anatol Maier, Andreas Spruck, Jürgen Seiler, Christian Riess
Forensic license plate recognition (FLPR) remains an open challenge in legal contexts such as criminal investigations, where unreadable license plates (LPs) need to be deciphered from highly compressed and/or low resolution footage, e. g., from surveillance cameras.
no code implementations • 28 Jul 2020 • Anatol Maier, Benedikt Lorch, Christian Riess
To this end, we propose to use Bayesian neural networks (BNN), which combine the power of deep neural networks with the rigorous probabilistic formulation of a Bayesian framework.