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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Automated creation of deep neural network models for image classification
 DOHNAL, Patrik
The aim of the thesis is to design and implement a system that can automatically create deep neural networks (DNN) models for image classification. Additionally, the aim is to review the current state-of-the-art and to validate the system's functionality on two different datasets. A genetic algorithm is used to find the best approximate DNN model. Additionally, several approaches to encode the genetic information of DNN models are explored. Furthermore, several experiments with the VGG-16 architecture were conducted to find the best possible system base. The thesis also includes a discussion on the practice of model training and how problems that can arise during the automatic training of DNN models are avoided. The implementation is written in Python with Tensorflow library.
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Detekce kategorie obsahu webové stránky prostřednictvím metod strojového učení.
 DOHNAL, Patrik
This bachelor thesis is focused on design and the implementation of the algorithm for classifying the websites into a several categories. The implementation of this software is written in Python. For classifying purposes I use machine learning models such as Naive Bayes classifier, K-Nearest neighbors and Support Vector Machines. Within the process it is assumed to collect my own dataset, wich will be used for training and testing purposes. Thesis also includes detailed description of the methods I uesd.
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See also: similar author names
11 Dohnal, Pavel
1 Dohnal, Pavel Bc.
18 Dohnal, Petr
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