|
|
Android application for subjective evaluation of video-sequences
Štarha, Dominik ; Přinosil, Jiří (referee) ; Číka, Petr (advisor)
This semestral thesis is focused on a group of four actually used video codecs, namely H.264, HEVC, VP8, VP9. The main objective is to decide on the basis of an evaluation by volunteers which one is the best suitable for video compression. The first part of thesis contains theoretical aspect od the issue. This includes a discussion about the the tested codecs, Android operating system description, performance of the Android Studio software and last but not least, introduction to the assessment methods, used to evaluate video quality, to guarantee the objectivity of the results. The secont part of thesis deals with the implementation of the testing procedure and following evaluation of the data obtained by the assessment.
|
|
|
Image similarity measuring using deep learning
Štarha, Dominik ; Šeda, Pavel (referee) ; Rajnoha, Martin (advisor)
This master´s thesis deals with the reseach of technologies using deep learning method, being able to use when processing image data. Specific focus of the work is to evaluate the suitability and effectiveness of deep learning when comparing two image input data. The first – theoretical – part consists of the introduction to neural networks and deep learning. Also, it contains a description of available methods, their benefits and principles, used for processing image data. The second - practical - part of the thesis contains a proposal a appropriate model of Siamese networks to solve the problem of comparing two input image data and evaluating their similarity. The output of this work is an evaluation of several possible model configurations and highlighting the best-performing model parameters.
|
|
|
Image similarity measuring using deep learning
Štarha, Dominik ; Šeda, Pavel (referee) ; Rajnoha, Martin (advisor)
This master´s thesis deals with the reseach of technologies using deep learning method, being able to use when processing image data. Specific focus of the work is to evaluate the suitability and effectiveness of deep learning when comparing two image input data. The first – theoretical – part consists of the introduction to neural networks and deep learning. Also, it contains a description of available methods, their benefits and principles, used for processing image data. The second - practical - part of the thesis contains a proposal a appropriate model of Siamese networks to solve the problem of comparing two input image data and evaluating their similarity. The output of this work is an evaluation of several possible model configurations and highlighting the best-performing model parameters.
|
|
|
Android application for subjective evaluation of video-sequences
Štarha, Dominik ; Přinosil, Jiří (referee) ; Číka, Petr (advisor)
This semestral thesis is focused on a group of four actually used video codecs, namely H.264, HEVC, VP8, VP9. The main objective is to decide on the basis of an evaluation by volunteers which one is the best suitable for video compression. The first part of thesis contains theoretical aspect od the issue. This includes a discussion about the the tested codecs, Android operating system description, performance of the Android Studio software and last but not least, introduction to the assessment methods, used to evaluate video quality, to guarantee the objectivity of the results. The secont part of thesis deals with the implementation of the testing procedure and following evaluation of the data obtained by the assessment.
|
guest ::
