Simple Incremental One-Class Support Vector Classification. - Kai Labusch; Fabian Timm; Thomas Martinetz (DAGM-Symposium, 2008)

Fast model selection for MaxMinOver-based training of support vector machines. - Fabian Timm; Sascha Klement; Thomas Martinetz (ICPR, 2008)

Welding Inspection using Novel Specularity Features and a One-class SVM. - Fabian Timm; Sascha Klement; Thomas Martinetz; Erhardt Barth (VISAPP (1), 2009)

Optical Inspection of Welding Seams. - Fabian Timm; Thomas Martinetz; Erhardt Barth (VISIGRAPP (Selected Papers), 2009)

Statistical Fourier Descriptors for Defect Image Classification. - Fabian Timm; Thomas Martinetz (ICPR, 2010)

Accurate, fast, and robust centre localisation for images of semiconductor components. - Fabian Timm; Erhardt Barth (Image Processing: Machine Vision Applications, 2011)

Non-parametric texture defect detection using Weibull features. - Fabian Timm; Erhardt Barth (Image Processing: Machine Vision Applications, 2011)

Illumination Correction for Image Stitching. - Sascha Klement; Fabian Timm; Erhardt Barth (IMAGAPP/IVAPP, 2011)

Accurate Eye Centre Localisation by Means of Gradients. - Fabian Timm; Erhardt Barth (VISAPP, 2011)

Novelty detection for the inspection of light-emitting diodes. - Fabian Timm; Erhardt Barth (Expert Syst. Appl., 2012)

Machine vision for inspection and novelty detection. - Fabian Timm (2012)

Learning multimodal fixed-point weights using gradient descent. - Lukas Enderich; Fabian Timm; Lars Rosenbaum; Wolfram Burgard (ESANN, 2019)

Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection. - Di Feng; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer (IV, 2019)

Can We Trust You? On Calibration of a Probabilistic Object Detector for Autonomous Driving. - Di Feng; Lars Rosenbaum; Claudius Gläser; Fabian Timm; Klaus Dietmayer (CoRR, 2019)

Inferring Spatial Uncertainty in Object Detection. - Zining Wang; Di Feng; Yiyang Zhou; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer; Masayoshi Tomizuka; Wei Zhan (IROS, 2020)

Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving. - Di Feng; Yifan Cao; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer (IV, 2020)

Where can I drive? Deep Ego-Corridor Estimation for Robust Automated Driving. - Thomas Michalke; Colin Wüst; Di Feng; Claudius Gläser; Maxim Dolgov; Fabian Timm (CoRR, 2020)

Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty. - Di Feng; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer (CoRR, 2020)

DeepReflecs: Deep Learning for Automotive Object Classification with Radar Reflections. - Michael Ulrich; Claudius Gläser; Fabian Timm (CoRR, 2020)

SYMOG: Learning symmetric mixture of Gaussian modes for improved fixed-point quantization. - Lukas Enderich; Fabian Timm; Wolfram Burgard (Neurocomputing, 2020)

Where can I drive? A System Approach: Deep Ego Corridor Estimation for Robust Automated Driving. - Thomas Michalke; Colin Wüst; Di Feng; Maxim Dolgov; Claudius Gläser; Fabian Timm (ITSC, 2021)

Holistic Filter Pruning for Efficient Deep Neural Networks. - Lukas Enderich; Fabian Timm; Wolfram Burgard (WACV, 2021)

Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges. - Di Feng; Christian Haase-Schütz; Lars Rosenbaum; Heinz Hertlein; Claudius Gläser; Fabian Timm; Werner Wiesbeck; Klaus Dietmayer (IEEE Trans. Intell. Transp. Syst., 2021)

Labels are Not Perfect: Inferring Spatial Uncertainty in Object Detection. - Di Feng; Zining Wang; Yiyang Zhou; Lars Rosenbaum; Fabian Timm; Klaus Dietmayer; Masayoshi Tomizuka; Wei Zhan (IEEE Trans. Intell. Transp. Syst., 2022)