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detection, segmentation, and quantification of diseases such as cancer, the generation of novel representations of pathology data for further processing, or the discovery of virtual biomarkers for patients
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) - Semantic 3D Scene Understanding - Face / Body Tracking, 3D Avatars - Non-Linear Optimization - Media Forensics / Fake News Detection How to Apply: Follow the instructions on our application platform: https
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19.09.2023, Wissenschaftliches Personal The Bienert Lab is part of the TUM School of Life Sciences of the Technical University of Munich located in Freising-Weihenstephan. The main objective
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pathology images and related medical data in order to detect, segment and quantify diseases such as cancer. Further applications are the discovery of new biomarkers and the prognosis of outcome for patients
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to understand how grazing influences tropical and subtropical grassland productivity and their stability, aiming to detect indicators of early restoration success. This work is conducted in collaboration with
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conduct experiments in the field to understand how grazing influences tropical and subtropical grassland productivity and their stability, aiming to detect indicators of early restoration success. This work
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
approaches for sustainability, new concepts for security and solutions for current latencies in communication networks. Find out more about the project under https://6g-life.de/ About us: At the Chair
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, ensuring individual mentoring and support throughout the entire sponsorship period. Application Papers Please find the application forms and further information on the application procedure here
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D