National Repository of Grey Literature 912 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Classification of global environmental systems according to the level of anthropogenic transformation
Hrdina, Aleš
The topic of the doctoral thesis is the development of a comprehensive classification of global environmental systems based on a geographical synthesis of abiotic, biotic and anthropogenic factors. The dramatic changes in the Earth's natural environment, the noticeable loss of biodiversity and the increasing impact of human activity in many different aspects raise the need for a comprehensive classification that provides an appropriate spatial framework for assessing the impacts of these changes. Several global classifications have been developed in the past, but most of them only work with various natural environmental gradients (especially climate or relief). However, most regions of the world have been so fundamentally affected or even completely transformed by human activity that the omission of anthropogenic factors in comprehensive environmental classifications may lead to erroneous conclusions. For this reason, new global environmental classifications have recently begun to emerge abroad that attempt to deal with anthropogenic changes to the natural environment and include them in a comprehensive assessment. The proposal of a methodology and the actual creation of the classification of global environmental systems based on abiotic gradients, biodiversity distribution and spatial...
Creating an Information Extension for the 3D Model of Tombstone – Finding the Most Effective Way
Adamcová, Alice
This article deals with creating a 3D model of a stone tombstone created with the terrestrial photogrammetry method and creating an information extension of this 3D model. Information extension is understood a 3D model classification considering different criteria, followed by classified 3D model visualisation. The paper mainly deals with testing the usefulness of different types of programs that can be used to create the information extension and based on this testing defines the most effective way of work.
The MDSR Vegetation Filter
Kučera, Jakub
This paper deals with the software implementation of a vegetation filter using the MDSR algorithm and its subsequent testing on a variety of pre-selected point clouds. The results of each filtering algorithm were compared visually in sections with the results of other conventionally used filtering algorithms. Comparisons were also made by calculating the root mean square deviations of the results of the conventional algorithms from the TIN surface generated from the MDSR filter results.
Classification of global environmental systems according to the level of anthropogenic transformation
Hrdina, Aleš ; Romportl, Dušan (advisor) ; Boltižiar, Martin (referee) ; Václavík, Tomáš (referee)
The topic of the doctoral thesis is the development of a comprehensive classification of global environmental systems based on a geographical synthesis of abiotic, biotic and anthropogenic factors. The dramatic changes in the Earth's natural environment, the noticeable loss of biodiversity and the increasing impact of human activity in many different aspects raise the need for a comprehensive classification that provides an appropriate spatial framework for assessing the impacts of these changes. Several global classifications have been developed in the past, but most of them only work with various natural environmental gradients (especially climate or relief). However, most regions of the world have been so fundamentally affected or even completely transformed by human activity that the omission of anthropogenic factors in comprehensive environmental classifications may lead to erroneous conclusions. For this reason, new global environmental classifications have recently begun to emerge abroad that attempt to deal with anthropogenic changes to the natural environment and include them in a comprehensive assessment. The proposal of a methodology and the actual creation of the classification of global environmental systems based on abiotic gradients, biodiversity distribution and spatial...
Emotion Recognition from Acted and Spontaneous Speech
Atassi, Hicham ; Přibil, Jiří (referee) ; Zahradník, Pavel (referee) ; Smékal, Zdeněk (advisor)
Dizertační práce se zabývá rozpoznáním emočního stavu mluvčích z řečového signálu. Práce je rozdělena do dvou hlavních častí, první část popisuju navržené metody pro rozpoznání emočního stavu z hraných databází. V rámci této části jsou představeny výsledky rozpoznání použitím dvou různých databází s různými jazyky. Hlavními přínosy této části je detailní analýza rozsáhlé škály různých příznaků získaných z řečového signálu, návrh nových klasifikačních architektur jako je například „emoční párování“ a návrh nové metody pro mapování diskrétních emočních stavů do dvou dimenzionálního prostoru. Druhá část se zabývá rozpoznáním emočních stavů z databáze spontánní řeči, která byla získána ze záznamů hovorů z reálných call center. Poznatky z analýzy a návrhu metod rozpoznání z hrané řeči byly využity pro návrh nového systému pro rozpoznání sedmi spontánních emočních stavů. Jádrem navrženého přístupu je komplexní klasifikační architektura založena na fúzi různých systémů. Práce se dále zabývá vlivem emočního stavu mluvčího na úspěšnosti rozpoznání pohlaví a návrhem systému pro automatickou detekci úspěšných hovorů v call centrech na základě analýzy parametrů dialogu mezi účastníky telefonních hovorů.
Automatic detection of ischemia in ECG
Noremberczyk, Adam ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
This thesis discusses the utilization of the artificial neural networks (ANN) for detection of coronary artery disease (CAD) in frequency area. The first part of this thesis is orientated towards the theoretical knowledge. Describes the issue of ECG pathological changes. ECQ are converted to frequency area. Described statistical methods and methods for automatic detection of CAD and MI. Explained the issue of the perceptron and ANN. The second deals with use of Neural Network Toolbox MATLAB®. This part focuses on counting and finding suitable parameters and making connection of band. At the end of the thesis UNS is used to detect ischemic parameters and the results are discussed. Average values for the best settings are 100% accuracy.
Overview of Actual Approaches to Classifications
Brezánský, Tomáš ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This bachelor thesis deals with an overview of current approaches to classifications. It describes various approaches to classifications and their algorithms, focuses on neural networks, Bayesian classifiers and decision trees. The main task of this work is to perform experiments with three classification algorithms, namely, the ID3 algorithm, the RCE neural network and the naive Bayesian classifier. The work contains experiments with given algorithms and evaluates the obtained results.
A convolutional neural network for image segmentation
Mitrenga, Michal ; Petyovský, Petr (referee) ; Jirsík, Václav (advisor)
The aim of the bachelor thesis is to learn more about the problem of convolutional neural networks and to realize image segmentation. This theme includes the field of computer vision, which is used in systems of artificial intelligence. Special Attention is paid to the image segmentation process. Furthermore, the thesis deals with the basic principles of artificial neural networks, the structure of convolutional neural networks and especially with the description of individual semantic segmentation architectures. The chosen SegNet architecture is used in a practical application along with a pre-learned network. Part of the work is a database of CamVid images, which is used for training. For testing, a custom image database is created. Practical part is focused on CNN training and searching for unsuitable parameters for network learning using SW Matlab.
Classification of the vascular tree in fundus images
Tebenkova, Iuliia ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
Retinal image analysis plays a very important role, as human gets around 90% of environment information with the help of eyes. Automation of process of retinal image analysis promotes to improve the efficiency of retinal medical examinations. The following thesis is dedicated to automatic classification methods of retinal vascular system images obtained from a digital fundus camera. Vessel classification method using classifier on the base of neural networks, which is trained and then tested on the retinal vessel segments, is investigated and implemented. In this thesis anatomical retinal survey, properties of image data from digital fundus camera and retinal image classification methods are briefly described. The last chapter is devoted to the evaluation of efficiency of retinal vessel classification with automatic methods.
Classification of sleep phases using polysomnographic data
Králík, Martin ; Kozumplík, Jiří (referee) ; Ronzhina, Marina (advisor)
Aim of this thesis is the classification of polysomnographic data. The first part of the thesis is a review of mentioned topic and also the statistical analysis of classification features calculated from real EEG, EOG and EMG for evaluating of the features suitability for sleep stages scoring. The second part is focused on the automatic classification of the data using artificial neural networks. All the results are presented and discussed.

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