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Relevant bibliographies by topics / Detekce objektů v obrazech

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Academic literature on the topic 'Detekce objektů v obrazech'

Author: Grafiati

Published: 28 June 2021

Last updated: 1 February 2022

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Dissertations / Theses on the topic "Detekce objektů v obrazech"

1

Kubínek, Jiří. "Detekce objektů v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-236646.

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This work is dedicated to methods used for object detection in images. There is a summary of several approaches and algorithms to solve this matter, especially AdaBoost algorithm with its improvement, WaldBoost and several features used for object detection. Vital part of this work is dedicated to extending training datasets for classifier training and extending the current object detection framework with histogram of gradients features implementation. Integral part of this work is analysis of results by experiments evaluation.

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2

Vylíčil, Radek. "Detektor objektů v obrazech založený na metodě C4." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-220400.

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This thesis deals with the image object detection using Contour cues. The text describes methods how to train and test object detector. The main contribution of this thesis consists in creation Feature extractor for creation object detector in Java programming. The functionality of object detector was demonstrated on medical images.

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3

Chrápek, David. "Učení a detekce objektů různých tříd v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236481.

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This paper is focused on object learning and recognizing in the image and in the image stream. More specifically on learning and recognizing humans or theirs parts in case they are partly occluded, with possible usage on robotic platforms. This task is based on features called Histogram of Oriented Gradients (HOG) which can work quite well with different poses the human can be in. The human is split into several parts and those parts are detected individually. Then a system of voting is introduced in which detected parts votes for the final positions of found people. For training the detector a linear SVM is used. Then the Kalman filter is used for stabilization of the detector in case of detecting from image stream.

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4

Mašek, Jan. "Detekce objektů v obraze s pomocí Haarových příznaků." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219794.

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This thesis deals with the image object detection using Haar--like features and AdaBoost algorithm. The text describes methods how to train and test an object detector. The main contributon of this thesis consists in creation image object detector in Java programming language. Created algorithms were integrated as plugin into the RapidMiner tool, which is widely used and known worldwide as tool for data mining. The thesis contains the instructions for created operators and few exaples for executing in RapidMiner tool. The functionality of image object detector was demonstrated on selected medical images.

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5

Mišta, Petr. "Hledání objektů v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217759.

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Detection of objects based on color is not commonly used method of computer vision. There are many methods thats deals with the detection of significant points, but the color information has been omitted. The goal of this thesis is to design method of the detection significant color image areas and these areas match up with areas detected in another image. I analyzed features of detectors required to identify the reciprocal correspondence of images, defined the color significance concept, described basic color models and their properties, and a design of statistically compiled data - based method was described. Algorithms for the detection of color use color models RGB and HSV. Correspondence of areas detected in different images is performedy Kohonen neural network. The first input vector can teach Kohonen neural network and the second vector is classified by this network. To remove erroneous classifications RANSAC method is used. As a result, the method can be used for basic and rapid determination of correspondence between images, or to speed up commonly used methods for detection of significant points. At the end of the thesis are presented programs, showing functionality and options of design methods. The designed algorithms have been developed in MATLAB.

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6

Matoušková, Barbora. "Detekce cizích objektů v rentgenových snímcích hrudníku s využitím metod strojového učení." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442486.

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Foreign objects in Chest X-ray (CXR) cause complications during automatic image processing. To prevent errors caused by these foreign objects, it is necessary to automatically find them and ommit them in the analysis. These are mainly buttons, jewellery, implants, wires and tubes. At the same time, finding pacemakers and other placed devices can help with automatic processing. The aim of this work was to design a method for the detection of foreign objects in CXR. For this task, Faster R-CNN method with a pre-trained ResNet50 network for feature extraction was chosen which was trained on 4 000 images and lately tested on 1 000 images from a publicly available database. After finding the optimal learning parameters, it was managed to train the network, which achieves 75% precision, 77% recall and 76% F1 score. However, a certain part of the error is formed by non-uniform annotations of objects in the data because not all annotated foreign objects are located in the lung area, as stated in the description.

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7

Řehánek, Martin. "Detekce objektů pomocí Kinectu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236602.

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With the release of the Kinect device new possibilities appeared, allowing a simple use of image depth in image processing. The aim of this thesis is to propose a method for object detection and recognition in a depth map. Well known method Bag of Words and a descriptor based on Spin Image method are used for the object recognition. The Spin Image method is one of several existing approaches to depth map which are described in this thesis. Detection of object in picture is ensured by the sliding window technique. That is improved and speeded up by utilization of the depth information.

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8

Johanová, Daniela. "Rozpoznávání objektů a gest v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234932.

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This thesis is focused on gesture recognition in video. The main purpose of this thesis was to create an algorithm and an application that can recognize selected gestures using a~video obtained through a~standard webcamera. The intention was to control an application program, such as video player. The approach used to achieve this goal was to exploit methods of feature extraction, tracking, and machine learning.

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9

Zavalina, Viktoriia. "Identifikace objektů v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220364.

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Master´s thesis deals with methods of objects detection in the image. It contains theoretical, practical and experimental parts. Theoretical part describes image representation, the preprocessing image methods, and methods of detection and identification of objects. The practical part contains a description of the created programs and algorithms which were used in the programs. Application was created in MATLAB. The application offers intuitive graphical user interface and three different methods for the detection and identification of objects in an image. The experimental part contains a test results for an implemented program.

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10

Králík, Martin. "Detekce objektů v obraze s pomocí rozšířené sady Haarových příznaků a histogramu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219796.

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This diploma thesis is focused on detection in images using extended set of Haar-like features and histogram-based method. At first is introduced a basic concept of extraction and classification image features. The next part bring own concept of image features based on Diffusion distance. Result of this work is implementation this methods in Rapidminer.

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