Prof. Dr. Tim Dahmen

Room

G2 1.13

Telephone

+49 7361 576-4184

Email Address

tim.dahmen[at]hs-aalen.de

Resume
Publications

AI workshop for SMEs

Scientific Scores

2004 - 2015 Education

2004 - today Professional Experience

Aalen University

DFKI GmbH, since 01/2014 leading Team ”Computational 3D Imaging”

Saarland University, Beginning of graduation

IMC AG

Xaitment GmbH, management of development projects for performance critical artificial intelligence (AI) components for computer games and simulations.

SAP Deutschland AG, During this employment assignments (among others) for: Hyundai Kia Motor Company, Seoul, South Korea; AMECO Beijing, China; Collectum AB, Stockholm, Sveden; Centrica plc, London, UK; Acceptance to top-talent carreer path of SAP Germany.

InTrace GmbH, development of performance critical realtime applications in computer graphics.

Professional Activities

Teaching & Supervision

Other Qualifications

Tim Dahmen, P. Trampert, D. Rubinstein, F. Boughorbel, C. Schlinkmann, M. Luschkova, S. Sandfeld

Further information

Tim Dahmen, C. Schorr, P. Goodarzi, F. Chen

Tim Dahmen

Tim Dahmen, C. Schlinkmann, M. Roland, C. Wolff, P. Trampert, P. Slusallek, S. Diebels

Further information

Tim Dahmen

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Prof. Dr. Tim Dahmen

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Dr.-Ing. in Computer Science

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W3 Professor for Machine Learning and Computer Vision

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Publications

Deep Neural Networks for Analysis of Microscopy ImagesSynthetic Data Generation and Adaptive Sampling

Neuroscope: An explainable ai toolbox for semantic segmentation and image classification of convolutional neural nets

Synthetic training data generation for deep learning based quality inspection

A GPU-based caching strategy for multi-material linear elastic FEM on regular grids

Advances in Sparse and Adaptive Scanning Electron Microscopy

Advances in Sparse and Adaptive Scanning Electron Microscopy

Prof. Dr. Tim Dahmen

Deep Neural Networks for Analysis of Microscopy ImagesSynthetic Data Generation and Adaptive Sampling

Neuroscope: An explainable ai toolbox for semantic segmentation and image classification of convolutional neural nets

Synthetic training data generation for deep learning based quality inspection

A GPU-based caching strategy for multi-material linear elastic FEM on regular grids

Advances in Sparse and Adaptive Scanning Electron Microscopy

Advances in Sparse and Adaptive Scanning Electron Microscopy

Deep Neural Networks for Analysis of Microscopy ImagesSynthetic Data Generation and Adaptive Sampling