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Rozpoznávání nemocí rostlin pomocí umělé inteligence
 Juliš, Adam ; Kubík, Tibor (referee) ; Bažout, David (advisor)
The aim of this work was to investigate the possibility of plant disease detection in the ab- sence of training data. The possibility of extracting the pattern of each disease and apply- ing these patterns to unknown plants was investigated. While still in the theoretical part of the thesis, this approach was found to be flawed. Furthermore, datasets with images of plant pathogens were analyzed and compared. An augmented image generator and several models were created over a smaller dataset validating existing approaches
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