National Repository of Grey Literature 60 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Degree of Parkinson's disease estimation based on acoustic analysis of speech
Ustohalová, Iveta ; Kiska, Tomáš (referee) ; Galáž, Zoltán (advisor)
The diploma thesis deals with the non-invasive analysis of progression of Parkinson´s disease using the acoustic analysis of speach. Hypokinetic dysarthria in connection with Parkinson´s disease as well as speech parameters are described in this work. Speech parameters are sorted according to the speech component they affect. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Based on obtained knowledge, in MATLAB development enviroment were created systém for UPDRS III scale estimation. The UPDRS III scale is based on subjective diagnosis given by the doctor. At first, one individual parameter is used for the UPDRS III scale value estimation. Then the feature selection using SFFS algorithm is applied to gain feature combination with minimal estimation errror. Attention i salso paid to correlation between individual symptoms and UPDSR III scale.
SAMSUNG Mobile Phones for year 2017 and their Competitiveness in the Czech Republic
Bendová, Kateřina ; Walek, Agata (referee) ; Baumgartnerová, Alena (advisor)
Tato bakalářská práce pojednává o mobilních telefonech firmy Samsung pro rok 2017. Je primárně zaměřena na technologie, které jsou v telefonech použity a jejich výhodami oproti konkurenci na českém trhu. Dále je v práci popsáno několik marketingových nástrojů, které Samsung používá v Českém maloobchodě, aby byly jeho produkty známější a viditelnější. Poslední kapitola je o roce 2017. Jsou zde popsány prodeje telefonů v roce 2017 a analýza potřeb zákazníků.
Face detection and recognition with use of Raspberry Pi
Rozhoňová, Andrea ; Mézl, Martin (referee) ; Hesko, Branislav (advisor)
The following bachelor thesis is focused on the face detection and recognition in an image. The theoretical part divides methods of detection and recognition into several groups and there is better description and explanation of these methods in this part. At the end of the theoretical part is summarized the current utilization of person recognition on the bases of its face in practice. In the practical part is first implemented method for face detection. It is combination of two approaches - approach using haar features and approach using templates of eye. The face recognition is provided by the convolutional neural network. In conclusion there are summarized principles and problems associated with implementation on microcomputer Raspberry Pi and there is also evaluated the success of implemented methods.
Biometric fingerprint liveness detection
Jurek, Jakub ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This project deals with general biometrics issues focusing on fingerprint biometrics, with description of dermal papillae and principles of fingerprint sensors. Next this work deals with fingerprint liveness detection issues, including description of methods of detection. Next this work describes chosen features for own detection, used database of fingerprints and own algorithm for image pre-processing. Furthermore neural network classifier for liveness detection with chosen features is decribed followed by statistic evaluation of the chosen features and detection results as well as description of the created graphical user interface.
Detection and Correspondence of Image Features
Hasmanda, Martin ; Kohoutek, Michal (referee) ; Říha, Kamil (advisor)
The main goal of this bachelor‘s thesis was obtain basic knowledge about image processing. Especially was this work specialized on features detection in images captured from different perspectives and for finding correspondences between those images. Preliminary were to be described the basic principles for understanding computer vision such as perspective projection, description model of the camera and two views geometry. From methods of the detection was introduced best-known and most widely used of the detectors Harris corner detector. He is independent of images rotation and he is analyzed in detail. Further was described SIFT detector, that is independent of images scale. In this work further be described to several methods for finding correspondences of images features. First were to be described and derived two basic transformation matrixes that arrange to the association with features of two images. The first homography matrix describes transformation of two 2D views and fundamental matrix. Fundamental matrix obtains from two images full information of captured 3D scene and projection matrixes of cameras. For to primary definition correspondences were to be used to methods SSD and NCC. These methods match correspondences after similarities surroundings of features. These methods unfiled correct assignment features. Therefore uses stochastic RANSAC algorithm. The RANSAC algorithm was in detail described in this work in basic form and further modified on MLESAC algorithm. This algorithm can find better correspondences than RANSAC. In the end was described simple application for implementation introduced methods.
Set of JavaApplets Demonstrations for Speech Processing
Kudr, Michal ; Karafiát, Martin (referee) ; Černocký, Jan (advisor)
The goal of the thesis is being familiar with methods a techniques used in speech processing. Using the obtained knowledge I propose three JavaApplets demonstrating selected methods. In this thesis we can find the theoretical analysis of selected problems.
Sleep scoring using artificial neural networks
Vašíčková, Zuzana ; Mézl, Martin (referee) ; Králík, Martin (advisor)
Hlavným cieľom semestrálnej práce je vytvorenie umelej neurónovej siete, ktorá bude schopná roztriediť spánok do spánkových epoch. Na začiatku je uvedené zhrnutie informácií o spánku a spánkových epochách. V ďalších kapitolách sa nachádza dôkladnejší prehľad metod na spracovávanie signálov a na klasifikáciu. Po zhrnutí teoretických znalostí potrebných na uskutočnenie praktickej časti práce boli na základe tohto rozboru vypočítané zo signálov potrebné znaky. Tieto znaky boli podrobené štatistickej analýze a na jej základe boli vybrané niektoré znaky, ktoré boli vhodné ako vstup do neurónovej siete, ktorá je po naučení schopná triediť spánkové epochy do príslušných fáz.
Interest Points Tracking in Video Sequence of Non-stationary Camera
Studený, Pavel ; Davídek, Daniel (referee) ; Horák, Karel (advisor)
The thesis deals with the issue of tracking feature points earned from videosequences of hand helded camera. The work is focused on the case of moving camera and static background, and events that are associated with this case and can occur. There is studied the movement of the camera, which is given its direction and speed. The aim of this work is the election and the subsequent implementation of three fundamentally different methods suitable for tracking feature points in case of moving camera and their comparison according to set criteria. On the basis of comparison will be under pre-defined conditions chosen algorithm that is best able to deal with tracing these points.
Automatic Photo Sorting
Weiser, Michal ; Španěl, Michal (referee) ; Beran, Vítězslav (advisor)
The purpose of this article is to show how intuitive can be work with pictures sorting. Drag&drop technology in combination with interactive picture moving makes this application easy to use. To sort pictures with some feature you just must drag magnetic attractor into some place in workspace and choose attracting feature with specific value. Pictures with alike value are attracted. Difference in values determines the distance between picture and attractor. Combination of many attractors can help you sort pictures in short time with just couple of clicks.
Optic flow software module design
Grulich, Jan ; Růžička, Michal (referee) ; Věchet, Stanislav (advisor)
This bachelor thesis is focused on the analysis of optical flow. The first part is dedicated to the theoretical analysis of the motion of image features. Especially important is finding quality features that can be tracked in a videosequence. Detailed mathematical description of the necessary algorithms is presented. The second part describes the software and its functions with the implemented algorithms. The main function is determining the distance of an object from the camera based on its velocity. Empirical tests of this function are presented.

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