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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Efficient implementation of deep neural networks
 Kopál, Jakub ; Mrázová, Iveta (advisor) ; Střelský, Jakub (referee)
In recent years, algorithms in the area of object detection have constantly been improving. The success of these algorithms has reached a level, where much of the development is focused on increasing speed at the expense of accuracy. As a result of recent improvements in the area of deep learning and new hardware architectures optimized for deep learning models, it is possible to detect objects in an image several hundreds times per second using only embedded and mobile devices. The main objective of this thesis is to study and summarize the most important methods in the area of effective object detection and apply them to a given real-world problem. By using state-of- the-art methods, we developed a traction-by-detection algorithm, which is based on our own object detection models that track transport vehicles in real-time using embedded and mobile devices. 1
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Local sharpness prediction and image segmentation
 Kopál, Jakub ; Šikudová, Elena (advisor) ; Horáček, Jan (referee)
The problem of automatic segmentation turned out to be complicated andtothisday, notcompletelysolved.Sinceitisacomplexproblem,thispaperis not- tryingtosolveitinitsmostgeneralform. Instead,itisfocusedonautomatic, bina- rypicturesegmentation,withtheoptiontochooseattributes, basedonwhich the seg- mentation should operate. Among these attributes are the focus and color of the picture. The results of the segmentation based on the assumption "focused object, blurry background" turned out to be very similar to the groundtruth in pictures, which fulfill this assumption. 1
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See also: similar author names
2 KOPAL, Jiří
1 Kopal, J.
1 Kopal, Jan
2 Kopal, Jiří
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