|
| |
|
|
Detection of Boxes in Image
Žitňanský, Adam ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
This thesis addresses the problem of cuboid detection, more specifically boxes detection in images. The main result is the implementation of a system for boxes detection based on corners and edges. The system consists of a CNN regression-based corner and edge points detector and decoder, which takes CNN output and turns it into a 2d model of the cuboid. As a part of this work also a a dataset of boxes with 550 images with corners and edges annotations was created
|
|
|
Urban Element Detection Using Satellite Imagery
Oravec, Dávid ; Herout, Adam (referee) ; Zlámal, Adam (advisor)
Táto práca sa zameriava na správnu detekciu objektov v satelitných snímkach pomocou konvolučných neuronových sietí. Cieľom práce je pomocou natrénovaného modelu detekovať bazény a tenisové ihriská v satelitných snímkach z rôznych miest. Model pracuje s dátami z 10 rôznych miest. Pri vypracovaní bol využitý model neurónovej siete RetinaNet a knižnica Detectron2. Model, ktorý sa podarilo vytrénovať, dokáže detekovať objekty s priemernou presnosťou (AP50) na úrovni 63,402 %. Práca môže byť prínosom v oblasti automatizovania získavania štatistík o povrchu zeme.
|
|
|
Running Motion Analysis
Eliáš, Radoslav ; Kolářová, Jana (referee) ; Goldmann, Tomáš (advisor)
Cieľom tejto práce je analyzovať pohyb a držanie tela pri behu. Systém pracuje so záznamom z dvoch kamier, zboku a zozadu. Využíva nástroj na detekciu postoja ľudského tela založenú na konvolučnej metóde. Práca porovnáva niekoľko detektorov. Výsledný systém používa detektor OpenPose a implementuje knižnicu s výpočtami pre rôzne metriky používane na ohodnotenie formy behu. Výsledky sú zobrazené v multiplatformnej aplikácii. Ohodnotená bola niekoľkými experimentmi na osobnej dátovej sade videí behu.
|
|
|
System for autonomous racetrack mapping
Soboňa, Tomáš ; Gábrlík, Petr (referee) ; Kopečný, Lukáš (advisor)
The focus of this thesis is to theoretically design, describe, implement and verify thefunctionality of the selected concept for race track mapping. The theoretical part ofthe thesis describes the ORB-SLAM2 algorithm for vehicle localization. It then furtherdescribes the format of the map - occupancy grid and the method of its creation. Suchmap should be in a suitable format for use by other trajectory planning systems. Severalcameras, as well as computer units, are described in this part, and based on parametersand tests, the most suitable ones are selected. The thesis also proposes the architectureof the mapping system, it describes the individual units that make up the system, aswell as what is exchanged between the units, and in what format the system output issent. The individual parts of the system are first tested separately and subsequently thesystem is tested as a whole. Finally, the achieved results are evaluated as well as thepossibilities for further expansion.
|
|
|
Application of Neural Accelerators on Rapsberry PI
Barna, Kristian ; Sekanina, Lukáš (referee) ; Vašíček, Zdeněk (advisor)
The presented bachelor thesis deals with the statistical evaluation of performance for hardward accelerator of deep neural networks. Describes convolutional neural networks along with mathematical calculations. Explains their acceleration and conversion to a format suitable for the Intel Movidius NCS accelerator. 8 hardware platforms and 22 neural network difficulties were compared experimentally. Up to 105-fold improvement was demonstrated in isolated inference of the MobileNetV2 network for the Raspber Pi platform using an accelerator. Performance between the tested platforms was also evaluated from an energy point of view. The application of facial identity demonstrated the conditions during real use. Possible limits of CNN acceleration on power-limited devices (Raspberry Pi) have been uncovered, especially due to improper selection of input image resolution. All measurements were evaluated by statistical procedures.
|
|
|
Detection of persons and evaluation of gender and age in image data
Dobiš, Lukáš ; Vičar, Tomáš (referee) ; Kolář, Radim (advisor)
Táto diplomová práca sa venuje automatickému rozpoznávaniu ludí v obrazových dátach s využitím konvolučných neurónových sieti na určenie polohy tváre a následnej analýze získaných dát. Výsledkom analýzy tváre je určenie pohlavia, emócie a veku osoby. Práca obsahuje popis použitých architektúr konvolučných sietí pre každú podúlohu. Sieť na odhad veku má natrénované nové váhy, ktoré sú vzápätí zmrazené a majú do svojej architektúry vložené LSTM vrstvy. Tieto vrstvy sú samostatne dotrénované a testované na novom datasete vytvorenom pre tento účel. Výsledky testov ukazujú zlepšenie predikcie veku. Riešenie pre rýchlu, robustnú a modulárnu detekciu tváre a ďalších ludských rysov z jedného obrazu alebo videa je prezentované ako kombinácia prepojených konvolučných sietí. Tieto sú implementované v podobe skriptu a následne vysvetlené. Ich rýchlosť je dostatočná pre ďalšie dodatočné analýzy tváre na živých obrazových dátach.
|
|
|
Recognition of Driving Lane Borders in Video from On Board Camera
Letovanec, Lukáš ; Bartl, Vojtěch (referee) ; Herout, Adam (advisor)
This thesis is dedicated to the issue of driving lane borders recognition in frames of an onboard camera. In this thesis, an architecture of a deep convolutional neural network is introduced, by means of which the said problem is dealt with. The net was trained on a large dataset using gradient descent algorithm. The trained model has demonstrated the ability to recognize borders of a driving lane well in different situations and conditions. The result of the thesis confirms that deep convolutional neural networks are a suitable tool for driving lane borders recognition.
|
|
|
Deep Learning for Object Detection
Pitoňák, Radoslav ; Dobeš, Petr (referee) ; Teuer, Lukáš (advisor)
This thesis analyzes different object detection methods which are based on deep neural networks. In the beginning, the convolutional neural networks are described and commonly used object detection methods are compared. In the following parts, the proposal and implementation of the object detection model trained on the specific dataset are described. In conclusion, the achieved results of this model are discussed and compared with the results of other methods.
|
|
|
Widget Recognition for Visual GUI Testing
Kisela, Sebastián ; Peringer, Petr (referee) ; Smrčka, Aleš (advisor)
The bachelor thesis analyzes current methods and tools used for user interfaces testing. The thesis sets specification requirements and design of the implemented tool. Implementation and limitations of the implemented tool, which is based on visual object recognition, are explained in a detailed way. Verification process of the tool is described at the end.
|
guest ::
