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Intracranial hemorrhage localization in axial slices of head CT images
Kopečný, Kryštof ; Chmelík, Jiří (referee) ; Nemček, Jakub (advisor)
This thesis is focused on detection of intracranial hemorrhage in CT images using both one-stage and two-stage object detectors based on convolutional neural networks. The fundamentals of intracranial hemorrhage pathology and CT imaging as well as essential insight into computer vision and object detection are listed in this work. The knowledge of these fields of studies is a starting point for the implemenation of hemorrhage detector. The use of open-source CT image datasets is also discussed. The final part of this thesis is a model evaluation on a test dataset and results examination.
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Application of cable robot
Bulenínec, Martin ; Dokoupil, Jakub (referee) ; Pivoňka, Petr (advisor)
The thesis deals with the changes of a cable robot to a manipulator. The mechanical changes are mostly about adding an active part to a moving platform with the ability to transfer objects and the effort to exchange the silicon cables for metal ones. The main part of the thesis is the proposed design and implementation of the algorithm for detection of a possible collision of the cable robot with an object in its working space.
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Image and Video Annotation as a Game
Skowronek, Ondřej ; Beran, Vítězslav (referee) ; Smrž, Pavel (advisor)
This master thesis is oriented on a problem of creating video and image annotations. This problem is solved by crowdsourcing approach. Crowdsourcing games were designed and implemented to make solution of this problem . It was proven by testing that these games are capable of creating high quality annotations. Launching these games on a larger scale could create large database of annotated videos and images.
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Deep-learning-based pattern detection in medical images
Koščová, Zuzana ; Vičar, Tomáš (referee) ; Jakubíček, Roman (advisor)
This Bachelor thesis deals with Deep-learning-based pattern detection in medical images. For better understanding of a subject artificial neural network and convolutional neural network (CNN) are described at first. Next chapter is focused on specific detection methods which use CNN. Within a bachelor thesis a dataset of abdominal CT a MRI scans was created. Faster R-CNN and YOLO algorithms were trained and tested on acquired scans for liver detection. Implementation of chosen methods took place in Python programming language using the Pytorch library. Finally, detection results and possible use in medicine are discussed.
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Procedurally Generated City
Panáček, Petr ; Šolony, Marek (referee) ; Kajan, Rudolf (advisor)
This paper deals with problem of procedurally generated city. There are described steps of creation of city. These steps are: road generation, extraction of minimal cycles in graph, division of lots and generation of buildings. Road and buildings are generated by L-system. Our system generate a city from input images, such as height map, map of population density and map of water areas. Proposed approaches are used for implementation of application for generation of city.
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Eye-blink detection
Jeništa, Petr ; Atassi, Hicham (referee) ; Vlach, Jan (advisor)
The merits of my Bachelor's Thesis is description of the theoretical principles of methods which are used for eye-blink detection. This work discribes methods for location of human face in a frame with the comlex background. The next principes of the work are different manners how we can find eyes in the frame and its sequential tracking. The last part is the eye analysis and the evaluation whether blinking went ahead or not.There are describes different intermedia which is used for processing of the numerical frame. At the close of the work is described the practical realization of some mentioned methods, thus the realization of algorithm which detects blinking eyes pair.
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Intracranial hemorrhage localization in axial slices of head CT images
Kopečný, Kryštof ; Chmelík, Jiří (referee) ; Nemček, Jakub (advisor)
This thesis is focused on detection of intracranial hemorrhage in CT images using both one-stage and two-stage object detectors based on convolutional neural networks. The fundamentals of intracranial hemorrhage pathology and CT imaging as well as essential insight into computer vision and object detection are listed in this work. The knowledge of these fields of studies is a starting point for the implemenation of hemorrhage detector. The use of open-source CT image datasets is also discussed. The final part of this thesis is a model evaluation on a test dataset and results examination.
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Deep-learning-based pattern detection in medical images
Koščová, Zuzana ; Vičar, Tomáš (referee) ; Jakubíček, Roman (advisor)
This Bachelor thesis deals with Deep-learning-based pattern detection in medical images. For better understanding of a subject artificial neural network and convolutional neural network (CNN) are described at first. Next chapter is focused on specific detection methods which use CNN. Within a bachelor thesis a dataset of abdominal CT a MRI scans was created. Faster R-CNN and YOLO algorithms were trained and tested on acquired scans for liver detection. Implementation of chosen methods took place in Python programming language using the Pytorch library. Finally, detection results and possible use in medicine are discussed.
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Application of cable robot
Bulenínec, Martin ; Dokoupil, Jakub (referee) ; Pivoňka, Petr (advisor)
The thesis deals with the changes of a cable robot to a manipulator. The mechanical changes are mostly about adding an active part to a moving platform with the ability to transfer objects and the effort to exchange the silicon cables for metal ones. The main part of the thesis is the proposed design and implementation of the algorithm for detection of a possible collision of the cable robot with an object in its working space.
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Procedurally Generated City
Panáček, Petr ; Šolony, Marek (referee) ; Kajan, Rudolf (advisor)
This paper deals with problem of procedurally generated city. There are described steps of creation of city. These steps are: road generation, extraction of minimal cycles in graph, division of lots and generation of buildings. Road and buildings are generated by L-system. Our system generate a city from input images, such as height map, map of population density and map of water areas. Proposed approaches are used for implementation of application for generation of city.
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