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National Repository of Grey Literature 1 records found  Search took 0.00 seconds. 
Active Learning for Image Classification
 Lorenzová, Kateřina ; Pilát, Martin (advisor) ; Křen, Tomáš (referee)
The thesis is a practical application of image analysis and classification methods, inspired by the behaviour of human eye. The method used doesn't require complete information of the analysed image. It uses autonomous agents that see only a part of the image instead. These agents themselves decide which other parts of the image they need to see for more precise result. The behavior of agents is controlled by a neural network, trained specifically for that purpose by an evolutionary learning algorithm. Data used for the training come from MNIST (2011), a database of handwritten numbers. This collection also contains a separate testing set, on which the behavior of autonomous agents was tested afterwards.
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