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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Mobilní aplikace pro podporu trénování silových sportů
 Košina, Simon ; Vaško, Marek (referee) ; Juránek, Roman (advisor)
The aim of this work is to create a mobile application for Android devices that provides athletes with real-time feedback during strength training in the form of velocity metrics for individual repetitions within a set of a certain exercise. Velocity based training is becoming increasingly popular both in practical applications and in research, where it has been demonstrated that these objective metrics can be used to estimate the intensity of a given set. The resulting application utilizes machine learning methods to detect weights plates loaded on a barbell in frames coming from the mobile device's camera and tracking their movement trajectory. Known size of the weight plates is used to calibrate the travelled distance. The algorithm operates in real-time, providing users with feedback during exercise sessions in the form of an auditory signal when a predefined threshold of selected velocity metric is reached.
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Robust Audio Dereverberation and Denoising
 Košina, Simon ; Skácel, Miroslav (referee) ; Szőke, Igor (advisor)
The goal of this thesis was to create a speech enhancement and dereverberation model for audio recordings coming from aircraft VHF communication. First, the thesis covers some theoretical grounds of machine learning and types of neural networks commonly used in such scenarios. Following is a description of the used framework, datasets and the implementation itself. Last chapters are focused on the performed experiments and their evaluation. At the end we talk about the future work that can be done in order to further improve the achieved results.
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Robust Audio Dereverberation and Denoising
 Košina, Simon ; Skácel, Miroslav (referee) ; Szőke, Igor (advisor)
The goal of this thesis was to create a speech enhancement and dereverberation model for audio recordings coming from aircraft VHF communication. First, the thesis covers some theoretical grounds of machine learning and types of neural networks commonly used in such scenarios. Following is a description of the used framework, datasets and the implementation itself. Last chapters are focused on the performed experiments and their evaluation. At the end we talk about the future work that can be done in order to further improve the achieved results.
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2 Košina, Stanislav
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