|
|
Topic Identification from Spoken TED-Talks
Vašš, Adam ; Ondel, Lucas Antoine Francois (referee) ; Kesiraju, Santosh (advisor)
Táto práca sa zaoberá problémom spracovania prirodzeného jazyka a následnej klasifikácie. Použité systémy boli modelované na TED-LIUM korpuse. Systém automatického spracovania jazyka bol modelovaný s použitím sady nástrojov Kaldi. Vo výsledku bol dosiahnutý WER s hodnotou 16.6%. Problém klasifikácie textu bol adresovaný s pomocou metód na lineárnu klasifikáciu, konkrétne Multinomial Naive Bayes a Linear Support Vector Machines, kde druhá technika dosiahla vyššiu presnosť klasifikácie.
|
|
|
Usage of advanced signal processing techniques for motor traffic safety enhancement
Beneš, Radek ; Říha, Kamil (referee) ; Atassi, Hicham (advisor)
This diploma thesis deals with the issue of the recognition of road signs in the video sequence. Such systems increase the traffic safety and are implemented by major car factories in the manufactured cars (Opel, BMW). First, the motivation for the utilisation of these systems is presented, followed by the survey of the current state of the art methods. Finally, a specific road-sign detection method is chosen and described in detail. The method uses advanced techniques of signal processing. Segmentation method in color space is used for sign detection and subsequent classification is accomplished by linear classification with optional use of PCA method. In addition, the method contains the prediction of road sign positions based on Kalman filtering. Implemented system yields relatively accurate results and overall analysis and discussion is enclosed.
|
|
|
Methods for Information Extraction in Text Documents
Sychra, Tomáš ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
Knowledge discovery in text documents is part of data mining. However, text documents have different properties in comparison to regular databases. This project contains an overview of methods for knowledge discovery in text documents. The most frequently used task in this area is document classification. Various approaches for text classification will be described. Finally, I will present algorithm Winnow that should perform better than any other algorithm for classification. There is a description of Winnow implementation and an overview of experimental results.
|
|
|
Topic Identification from Spoken TED-Talks
Vašš, Adam ; Ondel, Lucas Antoine Francois (referee) ; Kesiraju, Santosh (advisor)
Táto práca sa zaoberá problémom spracovania prirodzeného jazyka a následnej klasifikácie. Použité systémy boli modelované na TED-LIUM korpuse. Systém automatického spracovania jazyka bol modelovaný s použitím sady nástrojov Kaldi. Vo výsledku bol dosiahnutý WER s hodnotou 16.6\%. Problém klasifikácie textu bol adresovaný s pomocou metód na lineárnu klasifikáciu, konkrétne Multinomial Naive Bayes a Linear Support Vector Machines, kde druhá technika dosiahla vyššiu presnosť klasifikácie.
|
|
|
Topic Identification from Spoken TED-Talks
Vašš, Adam ; Ondel, Lucas Antoine Francois (referee) ; Kesiraju, Santosh (advisor)
Táto práca sa zaoberá problémom spracovania prirodzeného jazyka a následnej klasifikácie. Použité systémy boli modelované na TED-LIUM korpuse. Systém automatického spracovania jazyka bol modelovaný s použitím sady nástrojov Kaldi. Vo výsledku bol dosiahnutý WER s hodnotou 16.6%. Problém klasifikácie textu bol adresovaný s pomocou metód na lineárnu klasifikáciu, konkrétne Multinomial Naive Bayes a Linear Support Vector Machines, kde druhá technika dosiahla vyššiu presnosť klasifikácie.
|
|
|
Topic Identification from Spoken TED-Talks
Vašš, Adam ; Ondel, Lucas Antoine Francois (referee) ; Kesiraju, Santosh (advisor)
Táto práca sa zaoberá problémom spracovania prirodzeného jazyka a následnej klasifikácie. Použité systémy boli modelované na TED-LIUM korpuse. Systém automatického spracovania jazyka bol modelovaný s použitím sady nástrojov Kaldi. Vo výsledku bol dosiahnutý WER s hodnotou 16.6\%. Problém klasifikácie textu bol adresovaný s pomocou metód na lineárnu klasifikáciu, konkrétne Multinomial Naive Bayes a Linear Support Vector Machines, kde druhá technika dosiahla vyššiu presnosť klasifikácie.
|
|
|
Electronic Trading
Mikulenčák, Roman ; Szőke, Igor (referee) ; Černocký, Jan (advisor)
The work deals with an automatic trading system with recognition of candle formations using linear classification with adaptive training od weights. It explains the basics of trading, technical analysis and technical terms. It contains a description of algorithmic nature, program implementation and experiment with developed trading system. The selected strategy is compared to other approaches.
|
|
|
Methods for Information Extraction in Text Documents
Sychra, Tomáš ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
Knowledge discovery in text documents is part of data mining. However, text documents have different properties in comparison to regular databases. This project contains an overview of methods for knowledge discovery in text documents. The most frequently used task in this area is document classification. Various approaches for text classification will be described. Finally, I will present algorithm Winnow that should perform better than any other algorithm for classification. There is a description of Winnow implementation and an overview of experimental results.
|
|
|
Usage of advanced signal processing techniques for motor traffic safety enhancement
Beneš, Radek ; Říha, Kamil (referee) ; Atassi, Hicham (advisor)
This diploma thesis deals with the issue of the recognition of road signs in the video sequence. Such systems increase the traffic safety and are implemented by major car factories in the manufactured cars (Opel, BMW). First, the motivation for the utilisation of these systems is presented, followed by the survey of the current state of the art methods. Finally, a specific road-sign detection method is chosen and described in detail. The method uses advanced techniques of signal processing. Segmentation method in color space is used for sign detection and subsequent classification is accomplished by linear classification with optional use of PCA method. In addition, the method contains the prediction of road sign positions based on Kalman filtering. Implemented system yields relatively accurate results and overall analysis and discussion is enclosed.
|
guest ::
