National Repository of Grey Literature 45 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Mapping the occurrence of teaching martial activities in PE at primary schools and grammar schools in Prague
Sochor, Jakub ; Zdobinský, Adam (advisor) ; Pavelka, Radim (referee)
Title: Mapping the occurrence of teaching martial arts in physical education at primary schools, secondary schools and grammar schools in Prague. Objective: The goal of the research is to find out how education in P.E. classes reflects the recommendation of framework education programme about education of martial arts, what percentage of clasśes do martial arts take in P.E. and to describe current trends of implementing martial arts to the curriculum or discover the reasons behind not implementing from the P.E. teacher's perspective. Methods: Analysis of literature of the given topic. We chose a survey as a research instrument. Based on previously published survey, which asked about the education of martial arts at a smaller selection of schools in Moravian region (Reguli, Ďurech, Vít, 2007), we created a purposeful survey. The survey was made on a platform service survio.com and distributed via e-mail to individual headmasters. They passed on the survey to P.E. teachers Results: Based on the evaluation of the survey, it was found that 75 of 84 teachers involve combat activities in P.E. classes. Of all of the questioned, 48 respondents were men and 34 women. Most of our respondents were between 31-40 years old. Most respondents teach only at E.P.A., 48 in total. Falling techniques are included by...
Mapping the occurrence of teaching martial activities in PE at primary schools and grammar schools in Prague
Sochor, Jakub ; Zdobinský, Adam (advisor) ; Pavelka, Radim (referee)
Title: Mapping the occurrence of teaching martial arts in physical education at primary schools, secondary schools and grammar schools in Prague. Objective: The goal of the research is to find out how education in P.E. classes reflects the recommendation of framework education programme about education of martial arts, what percentage of clasśes do martial arts take in P.E. and to describe current trends of implementing martial arts to the curriculum or discover the reasons behind not implementing from the P.E. teacher's perspective. Methods: Analysis of literature of the given topic. We chose a survey as a research instrument. Based on previously published survey, which asked about the education of martial arts at a smaller selection of schools in Moravian region (Reguli, Ďurech, Vít, 2007), we created a purposeful survey. The survey was made on a platform service survio.com and distributed via e-mail to individual headmasters. They passed on the survey to P.E. teachers Results: Based on the evaluation of the survey, it was found that 75 of 84 teachers involve combat activities in P.E. classes. Of all of the questioned, 48 respondents were men and 34 women. Most of our respondents were between 31-40 years old. Most respondents teach only at E.P.A., 48 in total. Falling techniques are included by...
Automatic Estimation of Distance between Vehicles
Beran, Martin ; Špaňhel, Jakub (referee) ; Sochor, Jakub (advisor)
This thesis deals with the automatic estimation of distance between moving vehicles. The resulting files contain edited video showing the distance. The solution is implemented in C++.
Automatic Traffic Video Surveillance: Fine-Grained Recognition of Vehicles and Automatic Speed Measurement
Sochor, Jakub ; Elder, James (referee) ; Svoboda,, Tomáš (referee) ; Herout, Adam (advisor)
V rámci této dizertační práce se zaměřuji na Inteligentní dopravní systémy a Počítačové vidění - především automatické měření rychlosti a rozpoznání automobilů podle typů.  Rozpoznání automobilů podle typů je úkol, ve kterém system má predikovat přesný typ (např. Škoda Octavia combi mk2) pro daný obrázek automobilu. Publikoval jsem dva články, které popisují navržený přístup k tomuto problému a tvoří jádro této dizertace. Prezentovaná metoda je založena na 3D obalových kvádrech postavených okolo automobilů, které jsou následně využity pro rozbalení obrázku automobilu do roviny a tudíž normalizaci vstupu neuronové sítě, která dělá následné rozpoznání. Přístup byl dále rozpracován v druhé publikaci, kde je navržena metoda pro určení tohoto 3D obalového kvádru z jediného obrázku - tudíž není nutné mít zkalibrovanou kameru. Experimentální výsledky ukazují, že navržená metoda zlepšuje úspěšnost rozpoznání o 12 procentních bodů - chyba rozpoznání je redukována o 50 procent.Při měření rychlosti má systém za úkol odhadnout rychlost projíždějících aut z videa. Cílem je také, ať měření probíhá plně automaticky bez jakékoli manuální kalibrace. Jelikož neexistoval žádný dataset, který by obsahoval velké množství průjezdů s přesně změřenou rychlostí, tak jsme nejprve takovýto dataset pořídili. Dále jsem navrhnul metodu pro plně automatickou kalibraci dopravní dohledové kamery což umožňuje měřit rychlost automobilů pozorovaných touto kamerou. Metoda je založena na odhadu kalibrace pomocí detekovaných úběžníků scény a následného zarovnání 3D modelů několika běžných typů automobilů. Experimentální výsledky ukazují, že navržená metoda dosahuje průměrné chyby měření rychlosti 1,10 km/h. 
Fine-Grained Vehicle Recognition from Traffic Surveillance Camera
Mencner, Pavel ; Špaňhel, Jakub (referee) ; Sochor, Jakub (advisor)
The aim of this thesis is image based detection of vehicles from traffic surveillance camera and fine-grained vehicle type recognition (manufacturer and model). In the thesis the Unpack normalization method is implemented which transforms the vehicle image into its apparent flat representation in order to increase the classifier's success rate. The Unpack method make use of 3D bounding box of the vehicle. This bounding box is constructed during test period using the information of vehicle contour and direction toward vanishing points. The thesis involve accuracy comparison between direct and Unpack classification methods. The proposed solution is based on several related parts that benefit from convolutional neural networks. These parts are: vehicle detection from image data, estimation of the directions towards vanishing points solved as classification task, vehicle contour detection using convolutional Encoder-Decoder network and fine-grained vehicle type classification. Using Unpack based classification the 2% accuracy improvement against direct classification has been achieved, resulting in 86% overall success rate. The outcome of this thesis is fine-grained vehicle classification system that works with traffic surveillance video without any viewpoint limitations.
Synthetic Dataset Generator for Traffic Analysis
Svoreň, Ondrej ; Sochor, Jakub (referee) ; Herout, Adam (advisor)
This bachelor thesis deals with the creation and customization of synthetic dataset genera tor for traffic analysis. It focuses on traffic analysis by means of computer vision, methods and conditions of creating the generator of synthetic dataset, possible application of achie ved results in machine learning and additional development opportunities. Using available automobile photographs from the Czech Republic, Slovakia, Poland and Hungary, a synthe tic license plate number generator was created, which, after graphical adjustment and after joining with the vehicle photographs creates the resulting dataset for machine learning. The solution itself is divided into the three scripts written in Python using the OpenCV library. The resulting dataset serves as an input for the machine learning system to re-identify the license plate numbers from photographs captured in the flow of traffic.
Deep Learning for Facial Recognition in Video
Jeřábek, Vladimír ; Sochor, Jakub (referee) ; Hradiš, Michal (advisor)
This work deals with face recognition in video using neural networks. In the beginning, there is described the process of selection and verification of convolution neural network to generate feature vectors from images of different identities. In the next part, this work deals with the aggregation of feature vectors from video frames. Aggregation takes place through aggregation neural networks. At the end of this work, the results obtained by the aggregation methods are discussed.
Mobile Application for Studis BUT
Smyčka, Jan ; Sochor, Jakub (referee) ; Špaňhel, Jakub (advisor)
Bachelor thesis deals with the development of mobile application in Android for VUT information system. The theoretical part of the thesis describes Android operating system and its basic elements used in the application development process, the text also describes the architectural design of mobile applications. The main part of the thesis deals with the implementation of the application and its testing on the users. In the final part of the thesis, the application development and user testing are assessed, and further possible development of the application for the future is proposed.
Speed Measurement of Vehicles from Surveillance Camera
Jaklovský, Samuel ; Juránek, Roman (referee) ; Sochor, Jakub (advisor)
This master's thesis is focused on fully automatic calibration of traffic surveillance camera, which is used for speed measurement of passing vehicles. Thesis contains and describes theoretical information and algorithms related to this issue. Based on this information and algorithms, a comprehensive system design for automatic calibration and speed measurement was built. The proposed system has been successfully implemented. The implemented system is optimized to process the smallest portion of the video input for the automatic calibration of the camera. Calibration parameters are obtained after processing only two and half minutes of input video. The accuracy of the implemented system was evaluated on the dataset BrnoCompSpeed. The speed measurement error using the automatic calibration system is 8.15 km/h. The error is mainly caused by inaccurate scale acquisition, and when it is replaced by manually obtained scale, the error is reduced to 2.45 km/h. The speed measuring system itself has an error of only 1.62 km/h (evaluated using manual calibration parameters).
Image Compression with Neural Networks
Teuer, Lukáš ; Sochor, Jakub (referee) ; Hradiš, Michal (advisor)
This document describes image compression using different types of neural networks. Features of neural networks like convolutional and recurrent networks are also discussed here. The document contains detailed description of various neural network architectures and their inner workings. In addition, experiments are carried out on various neural network structures and parameters in order to find the most appropriate properties for image compression. Also, there are proposed new concepts for image compression using neural networks that are also immediately tested. Finally, a network of the best concepts and parts discovered during experimentation is designed.

National Repository of Grey Literature : 45 records found   1 - 10nextend  jump to record:
See also: similar author names
6 SOCHOR, Jan
6 Sochor, Jan
4 Sochor, Jiří
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