BISON
Brain-computer interface based interaction …
BISON – Brain-computer interface based interaction concepts for controlling surgical microscopes in neurosurgery
The aim of the project BISON is the conception and implementation of an intuitive control of operating microscopes by measured brain activity without the use of hands. The developed solution is based on non-invasive methods for measuring the electrical activity of the brain, using headsets for measuring the electroencephalogram (EEG).
ProSec
Proven Security for systems with human interaction
ProSec – Proven Security for systems with human interaction
The aim of the project ProSec (Proven Security) is to make the latest research results from the formal analysis of systems usable in the assessment of (data) security. The innovation of this approach is that, for the first time, not only hardware and software components are examined with mathematical precision, but also the actions of the people who operate in the systems – and usually make the most serious mistakes for security.
CellPhaser
An intuitive machine learning solution for the …
CellPhaser – An intuitive machine learning solution for the analysis of holographic cell images
The CellPhaser functions as the software core of the “CellFace” project at the Central Institute for Translational Cancer Research (TranslaTUM), with the goal of establishing DHM-based, label-free flow cytometry as a platform technology for cellular diagnostics.
S³ – Building Blocks for Security in Industrial IoT
The goal of this project is therefore a solution that integrates existing machines safely into smart factories. The focus is on functional transparency and easy usability by reducing complexity. The basis is a low cost embedded platform, which acts as a security gateway and can protect network traffic transparently and efficiently. In addition, further important and security-relevant aspects are to be researched, which extend the basic platform in a meaningful way and increase its suitability for practical use.
QUOCA
Quality-driven data integration in Semantic Data Lakes
QUOCA – Quality-driven data integration in Semantic Data Lakes
The goal of the project “QUOCA – Quality-Driven Data Integration in Semantic Data Lakes” is to determine the quality of data from a variety of heterogeneous data sources in the context of Big Data and to use the knowledge about quality in the data integration process to support downstream processes such as data analytics and machine learning and to improve the generated insights. The approach is based on Semantic Data Lakes as a technology for integrating large amounts of data from a multitude of data sources via a uniform interface.
BISON – Brain-computer interface based interaction concepts for controlling surgical microscopes in neurosurgery
The aim of the project BISON is the conception and implementation of an intuitive control of operating microscopes by measured brain activity without the use of hands. The developed solution is based on non-invasive methods for measuring the electrical activity of the brain, using headsets for measuring the electroencephalogram (EEG).
ProSec – Proven Security for systems with human interaction
The aim of the project ProSec (Proven Security) is to make the latest research results from the formal analysis of systems usable in the assessment of (data) security. The innovation of this approach is that, for the first time, not only hardware and software components are examined with mathematical precision, but also the actions of the people who operate in the systems – and usually make the most serious mistakes for security.
CellPhaser – An intuitive machine learning solution for the analysis of holographic cell images
The CellPhaser functions as the software core of the “CellFace” project at the Central Institute for Translational Cancer Research (TranslaTUM), with the goal of establishing DHM-based, label-free flow cytometry as a platform technology for cellular diagnostics.
S³ – Building Blocks for Security in Industrial IoT
The goal of this project is therefore a solution that integrates existing machines safely into smart factories. The focus is on functional transparency and easy usability by reducing complexity. The basis is a low cost embedded platform, which acts as a security gateway and can protect network traffic transparently and efficiently. In addition, further important and security-relevant aspects are to be researched, which extend the basic platform in a meaningful way and increase its suitability for practical use.
QUOCA – Quality-driven data integration in Semantic Data Lakes
The goal of the project “QUOCA – Quality-Driven Data Integration in Semantic Data Lakes” is to determine the quality of data from a variety of heterogeneous data sources in the context of Big Data and to use the knowledge about quality in the data integration process to support downstream processes such as data analytics and machine learning and to improve the generated insights. The approach is based on Semantic Data Lakes as a technology for integrating large amounts of data from a multitude of data sources via a uniform interface.