- About
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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
Search results
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Význam positivního výběru pro pěstební praxi lesnickouVyskot, Miroslav January 1949 (has links)
No description available.
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Tlumivost půd jako jeden z ukazatelů její kvalityMartinec, Jiří January 2010 (has links)
No description available.
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Analýza vlivu kování na zatékavost a spárovou průvzdušnost okenSláčík, Petr January 2007 (has links)
No description available.
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Klasifikace a shlukování ekonomických dat pomocí metod strojového učeníKosová, Andrea January 2013 (has links)
No description available.
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Návrh geostezky na NovojičínskuJurečková, Alena January 2010 (has links)
No description available.
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Geobiocenologické charakteristiky jednotek stanovišť "přirozených borů" v oblasti Třeboňské pánveZeman, Miroslav January 2011 (has links)
No description available.
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Optimalizace řízení zásob brněnské divize Přístrojové transformátory a senzory společnosti ABB, s.r.o.Chlubnová, Iveta January 2012 (has links)
No description available.
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Klasifikační metody pro data z mikročipů / Classification Methods for Micriarrays DataHudec, Vladimír January 2011 (has links)
This paper discusses about the data obtained from gene chips and methods of their analysis. Analyzes some methods for analyzing these data and focus on the method of "Random Forests". Shows dataset that is used for specific experiments. Methods are realized in R language environment. Than they are tested, and the results are presented and compared. Results with method "Random Forests" are compared with other experiments on same dataset.
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Automatické rozpoznávání zpěvu ptákůBřenek, Roman January 2014 (has links)
This master thesis deals with methods of automatic recognition of bird species by their voices. In first, I defined the database of records and created a reference data by handmade evaluation. The next step is to find the optimal features for describing a bird singing. I use a Human Frequency cepstral Coefficients (HFCC). For the best accuracy of recognition is necessary to correctly classify a bird's vocalization from a non-vocalization segments. The VAD system is based on an algorithm k-Nearest Neighbours. The last step describes the system based on Hidden Markov Models which allows to recognize the concrete bird species from the parts of bird's singing.
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Modul pro vyhledávání nevhodných obrázkůŽurek, Aleš January 2015 (has links)
This work is focused on classifying photos which are uploaded on dating service Lidé.cz. Pictures are classified into two categories based on whether they contain pornographic content or not. Convolutional neural networks are used for classification and these neural networks are taught by using Caffe framework. The results of this work fulfilled all requirements from Seznam.cz, a.s. company. Classification accuracy of the best model on created testing dataset with 5643 photos was 93,64 % and the time for classification of photography is low enough to perform classification in real time. The first part contains an analysis of the current approaches for image classification. The second part focuses on the analysis and draft of the solution and the third part describes the implementation of the solution and the testing of neural networks models.
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