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Branch detail

Computer Science and Engineering


Abbreviation: DVI4
Specialisation: -
Length of Study: -
Programme: Computer Science and Engineering
Faculty: Faculty of Information Technology
Academic year: 2017/2018
Accredited from: 30.6.2007
Accredited until: 31.12.2020
Profile of the branch:
The goal of the doctoral study programme is to provide outstanding graduates from the MSc study programme with a specialised university education of the highest level in certain fields of information technology, including especially the areas of information systems, computer-based systems and computer networks, computer graphics and multimedia, and intelligent systems. The education obtained within this study programme also comprises a training and attestation for scientific work.
Key learning outcomes:

  • Graduates from the doctoral study programme are trained to independently work in research, development, or management.
  • They are able to solve and/or to lead teams solving advanced conceptual, research, development, or production problems in the area of contemporary information technology and its applications.
  • They can be engaged to work on creative tasks, to lead research and development teams, or to work in management of companies or organizations whenever there are required abilities to work in an independent and creative way, to analyze complex problems, and to propose and realize new and original solutions. Graduates from the doctoral study programme can also teach and/or scientifically work at universities.
Occupational profiles of graduates with examples:
Not applicable.
Branch supervisor: prof. RNDr. Milan Češka, CSc.
Issued topics of Doctoral Study Program:
  1. Advanced Algorithms of Computer Graphics

    The topic focuses algorithms of computer graphics and generally computer image synthesis. Its main goal is to research algorithms so that their features and application possibilities are better understood, so that they are deeply analyzed, so that they are improved or newly created, and so that they are efficiently implemented e.g. in CPU, in CPU with acceleration through SSE instructions, in embeded systems, in embedded systems with FPGA, or in other systems, such as x86/64, ARM, Xeon PHI, or other cores. Algorithms of interest include 3D model processing and acquisition. The programming work is expected in C, C++, C#, assembly language, CUDA, OpenCl, VHDL, or other. The algorithms of interest include:

    • rendering using selected computer graphics methods (such as ray tracing, photon mapping, direct rendering of "point clouds", etc.),
    • reconstruction of 3D scenes from images and/or video, eventually also fusing with other sensors, such as LIDAR,
    • new algorithms of graphics and image synthesis suitable for mobile and embedded systems,
    • modern algorithms of geometry suitable for applications in cpmputer graphics and perhaps also 3D printing,
    • methods of video processing in the form of "cartoon", with false colours, with simulation of painterly techniques, etc., 
    • emerging algorithms of 3D synthesis, holography, wavelet transform, frequency transform, etc.

    After mutual agreement, individually selected algorithms can be considered as well as soon as they do belong to the general topic.


    Tutor: Zemčík Pavel, prof. Dr. Ing.
  2. Algorithms of Advanced Image and Video Processing

    The topic focuses algorithms of image and video processing. Its main goal is to research algorithms so that their features and application possibilities are better understood, so that they are deeply analyzed, so that they are improved or newly created, and so that they are efficiently implemented e.g. in CPU, in CPU with acceleration through SSE instructions, in embeded systems, in embedded systems with FPGA, or in other systems. The programming work is expected in C, C++, C#, assembly language, CUDA, OpenCl, or VHDL. The algorithms of interest include:

    • recognition of scene contents, events, and general semantics of video sequences,
    • classification of video sequences through deep convolution networks neural networks, space-time features, etc.,
    • object tracking in video using modern methods (such as TLD or particle tracking)
    • assessment of video content similarities and its contents e.g. through mutual information, semantics analysis,
    • new algorithms of video Processing suitable e.g. for mobile technology and/or embedded systems,
    • algorithms of video compression and analysis through frequency or wavelet transforms or similar methods...

    After mutual agreement, individually selected algorithms can be considered as well as soon as they do belong to the general topic.

    Tutor: Zemčík Pavel, prof. Dr. Ing.
  3. Analysis of Presence and Motion of Pedestrians in Video

    • Research and development of computer vision algorithms.
    • Focus on videos from interior/exterior surveillance cameras.
    • Research of algorithms avoiding user input.
    • Implementation of experimental prototypes.
    • Design and development of application demonstrators.

    Tutor: Herout Adam, prof. Ing., Ph.D.
  4. Augmented Reality on Mobile Devices

    The goal of the work is to research and create algorithms that will allow for running augmented reality on mobile (ultramobile) devices. It mainly concerns algorithms of pose estimation in the space by the means of computer vision and by using sensors embedded in the device. Furthermore, the work will elaborate on algorithms of rendering of virtual elements into the real-world scene and on applications of augmented reality on mobile devices.

    Tutor: Herout Adam, prof. Ing., Ph.D.
  5. Dependability Issues of Operating Systems and Applications They Control

    Modern operating systems (OS) must meet many requirements not only in terms of flexibility and efficiency of their execution on recent computing platforms, but also in terms of dependability of their kernels and services they provide to the application layer. The aim of the project is:

    • to analyze the actual state in the area of dependability of OS kernels / services,
    • to identify (in terms of dependability) negative effects and their impact to dependability of the application layer,
    • to propose a method for increasing dependability of OS kernels / services,
    • to evaluate an impact of the method to dependability of OS kernels / services and operation of the application layer.

    The project can be oriented into various directions, such as low-power applications / OS or application / OS designed to run in an embedded or a multi-core environment. During the project, a "conventional" OS such as Unix, Linux, Android, Windows, iOS or a specialized OS such as QNX, uC/OS-I (II, III), FreeRTOS, MQX can be utilized.

    Tutor: Strnadel Josef, Ing., Ph.D.
  6. Detection and Re-Identification of Objects in Image and Video

    • Omnidirectional object detection in real time
    • Re-identification of detected objects, e.g. in shots from different cameras or at different points in time
    • Focused on statinary surveillance cameras
    • Focused on automatic traffic surveillance

    Tutor: Herout Adam, prof. Ing., Ph.D.
  7. Interaction of speech recognition and data mining

    Speech recognition systems are nowadays rarely used alone, but are parts of more complex data processing chains, both in military-security and business scenarios. Typically, they are integrated with a machine translation system and the following data-mining, for example topic detection, sentiment/emotion analysis or business data extraction. As many of these systems are nowadays based on DNNs or their variants, there is a possibility of joint training of such system optimizing the final goal of the system.

    The proposal is related to ongoing EU H2020 project Bison, and US DARPA funded Lorelei project.

    Tutor: Černocký Jan, doc. Dr. Ing.
  8. Recognition and Tracking of Human Body in Video

    • Study and research of algorithms of computer vision.
    • Focus on detection, recognition, and pose estimation of a human body.
    • Tracking of parts of human body in time, using temporal coherence.
    • Design and implementation of algorithms working in real time.

    Tutor: Herout Adam, prof. Ing., Ph.D.
  9. Security and Privacy of Internet of Things

    Many IoT devices are vulnerable to cyber attacks. Legacy devices were not designed under security considerations. Due to cost/energy constraints IoT devices have limited processing power which may be challenging for detection and prevention of attacks. IoT devices are mostly based on open technologies, but not hardened enough for the Internet environment. IoT devices employees wireless interfaces that enable an attacker to easy access the device. Iot devices are updated irregularly or never. IoT domains often involve information about the users. Thus information leakage is some serious problem too. 

    To address the issue of security and privacy in IoT environment, there is a need for establishing a robust security architecture for heterogeneous environments.

    This topic aims at the analysis of security and privacy problems in a selected IoT domains followed by the proposal for a security architecture and the demonstration of its security properties by developing and evaluating its experimental implementation.The goal the thesis is to deliver a proof of concept of security architecture for IoT devices and demonstrates its qualitative security parameters. 

    Tutor: Ryšavý Ondřej, doc. Ing., Ph.D.
  10. User Experience and Modern User Interfaces

    • Study and design of advanced web and mobile user interfaces.
    • Validation, optimization, and user testing of web and mobile user interfaces.
    • Statistical processing of data collected from human respondents / users.
    • Design, development, and deployment of practically usable web/mobile system / user interface.

    Tutor: Herout Adam, prof. Ing., Ph.D.
  11. Visual Geo-Localization on Mobile Devices

    The project deals with geo-localization of mobile devices in unknown environments using computer vision and computer graphics methods. The aim is to investigate and develop new image registration techniques (with geo-localized image database or 3D terrain model). The goal is an efficient implementation of proposed methods on mobile devices as well as search for additional applications in the area of image processing, computational photography, and augmented reality.

    Tutor: Čadík Martin, doc. Ing., Ph.D.
  12. An amount of data in computer networks has dramatically increased in the last few years, imposing problems for the typical Network Traffic Monitoring and Analysis (NTMA) tools. For fast and accurate anomaly detection, identification of network attacks and intrusions, the NTMA tools must be able to cope with thousands of events per second and deal with an extensive database of historical data.
    This project aims at researching and developing novel scalable techniques capable of analyzing both online network traffic data streams and offline traffic datasets.

    Tutor: Ryšavý Ondřej, doc. Ing., Ph.D.

Course structure diagram with ECTS credits

Study plan wasn't generated yet for this year.