Institute of Information Theory and Automation

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Department: Duration: 2019 - 2021 Grantor: GACR
The project deals with design of novel methods for control of large-scale and multi-agent systems in presence of nonlinearities, quantizations and time delay, with a focus on systems controlled by communication networks. A special attention is paid to systems composed of identical subsystems.
Department: ZOI Duration: 2018 - 2022 Grantor:
PROVENANCE is an intermediary-free solution that gives greater control to users of social media and underpins the dynamics of social sharing in values of trust, openness, and fair participation. PROVENANCE will use blockchain to record multimedia content that is uploaded and registered by content creators or identified for registration by the PROVENANCE Social Network Monitor.
Department: AS Duration: 2018 - 2021 Grantor: MSMT
The proposed project aims to contribute to theoretical and algorithmic development of cooperation and negotiation aspects while respecting agent imperfection and deliberation. The targeted solution should be applicable to decentralised dynamic DM under complexity and uncertainty. It will support a single agent acting within a network of strategically interacting agents.
Department: ZS Duration: 2018 - 2021 Grantor: FG
The objective of FitOptiVis is to develop a cross-domain approach for smart integration of image- and video-processing pipelines for CPS covering a reference architecture, supported by low-power, high-performance, smart devices, and by methods and tools for combined design-time and run-time multi-objective optimisation within system and environment constraints.
Department: ZS Duration: 2018 - 2021 Grantor: FG
The WAKEMEUP project objective is to set-up a pilot line for advanced microcontrollers with embedded non-volatile memory, design and manufacturing for the prototyping of innovative applications for the smart mobility and smart society domains. The already defined microcontrollers with 40nm embedded flash technology will be consolidated to build a solid manufacturing platform.
Department: MTR Duration: 2018 - 2020 Grantor: GACR
Graded properties are ubiquitous in human discourse and reasoning. They are characterized by the fact that they may apply with different intensity to different objects. Typical examples are vague properties (e.g.
Department: AS Duration: 2018 - 2020 Grantor: GACR
Optimal processing of distributed knowledge is key agenda in machine learning, signal processing and control, driven by sensor networks for smart environments, autonomous agents and distributed infrastruktures (clouds, Internet) serving the tnternet of things. Nodes may communicate via partially specied probability distributions (moments, etc.).
Department: ZOI Duration: 2018 - 2020 Grantor: GACR
Objects moving fast with respect to the camera appear blurred when observed. Surprisingly this common phenomenon has not yet been considered and analyzed by the computer vision community. It is the blur that encodes information about the object motion properties. Instead of considering blur as a nuisance, the project proposes to take it as a cue for detection and tracking of fast moving objects.
Department: AS Duration: 2018 - 2020 Grantor: GACR
Anomaly detection, which aims to identity samples very different from majority, is an important tool of unsupervised data analysis. Currently, most methods for anomaly detection use relatively simple shallow models without any complex layers and hierarchies.
Department: MTR Duration: 2018 - 2019 Grantor: AV_GA
The goal of the project is to establish the research cooperation between the mutually complementary Taiwan and Czech research teams. The research is oriented to the development and verification of a new data mining technique based on probabilistic compositional models, the theory of which was developed by the Czech partner in the last decade.
Department: ZOI Duration: 2018 - 2021 Grantor: GACR
The proposal falls into the area of computer image analysis and pattern recognition. It is focused on special type of data - multidimensional vector and tensor fields. Vector fields may describe particle velocity, optical/motion flow, image gradient, deformation/condutivity/diffusion tensors, and other phenomena.
Department: ZOI Duration: 2018 - 2020 Grantor: TACR
The goal of the project is to develop new methods for colour image acquisition and processing and to apply the results of this research in selected practical applications. The project is aimed at colour image with high colour resolution, with up to several tens colour components.
Department: ZOI Duration: 2018 - 2023 Grantor:
Department: ZOI Duration: 2018 - 2021 Grantor: GACR
The topic of this project is to develop efficient algorithms for robust image description and for recovering a clear image from its degraded version.