no code implementations • 25 Sep 2019 • Kamila Abdiyeva, Martin Lukac, Kanat Alimanov
Convolutional Neural Networks (CNN) have achieved state-of-the-art performance in different computer vision tasks, but at a price of being computationally and power intensive.
no code implementations • 1 Sep 2017 • Martin Lukac, Aigerim Bazarbayeva, Michitaka Kameyama
In order to improve the accuracy of this method in the verification task, we include the context information such as location, type of environment etc.
no code implementations • 12 Aug 2016 • Martin Lukac, Kamila Abdiyeva, Michitaka Kameyama
In this paper we discuss certain theoretical properties of algorithm selection approach to image processing and to intelligent system in general.
no code implementations • 12 Aug 2016 • Martin Lukac, Kamila Abdiyeva, Michitaka Kameyama
That is, let there be a set A of available algorithms for symbolic segmentation, a set of input features $F$, a set of image attribute $\mathbb{A}$ and a selection mechanism $S(F,\mathbb{A}, A)$ that selects on a case by case basis the best algorithm.
no code implementations • 29 May 2015 • Martin Lukac, Kamila Abdiyeva, Michitaka Kameyama
In this paper we present an alternative approach to symbolic segmentation; instead of implementing a new method we approach symbolic segmentation as an algorithm selection problem.