National Repository of Grey Literature 12 records found  previous11 - 12  jump to record: Search took 0.00 seconds. 
Deep Learning for Medical Image Analysis
Bíl, Tomáš ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
The goal of this thesis is developing convolutional neural network which is able to classify if x-ray images are suitable for cephalometry analysis. Four networks were created and trained on a dataset for this purpose. Two of them are VGG type, one is based on UNet and one is Resnet. The dataset was generated from ct scan images. VGG network with four blocks has got the best results.  Measured accuracy performed on test dataset is 97%.
WaldBoost on GPU
Polok, Lukáš ; Mikolov, Tomáš (referee) ; Hradiš, Michal (advisor)
Image recognition and machine vision in general is quickly evolving field, due boom of cheap and powerful computation technologies. Image recognition has many different applications in wide spectrum of industries, ranging from communications trough security to entertainment. Algorithms for image recognition are still evolving and are often quite computationaly demanding. That is why some of authors deal with implementing the algorithms on specialized hardware accelerators. This work describes implementation of image recognition using the WaldBoost algorithm on the graphic accelerator (GPU) platform.

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