National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Behavioral Genetics of Mate Preferences
Fischer, Martin ; Štěrbová, Zuzana (advisor) ; Bosman, Dita (referee)
Mate preferences are a multidimensional set of mental representations about the characteristics of a potential partner. The aim of this theoretical work is to present the current state of knowledge in the field of inheritance of mate preferences. While there have been several studies that have attempted to estimate the contribution of genetic components and (shared and non-shared) environment to mate preferences and mate choice, the current research suggests the key role of gene-environment interactions. This thesis provides a brief introduction to behavioral genetics and introduces the basic principles of heritability of mate preferences. All studies previously conducted on humans are dealt with in greater detail. However, the environment appears to play a more significant role than direct genetic influences. Consequently, other mechanisms of ontogeny of mate preferences, of which this environment may be composed (i.e. imprinting-like effect, associative learning, social learning, active parental influence on mate choice), are presented. The thesis is concluded with a synthesis of findings on individual mechanisms of the emergence and development of mate preferences and their potential interactions. Each mechanism may explain a relatively small part of the emergence of mate preferences, yet they...
Detection of Graffiti Tags in Image
Fischer, Martin ; Kodym, Oldřich (referee) ; Špaňhel, Jakub (advisor)
The aim of this work is to compare different approaches of computer vision with the intention of automatic detection of graffiti tags in the image. The solution was based on models based on neural networks. Both the proven detection models and the experimental models were tested here. The most accurate one (Faster R-CNN) achieved an accuracy of 83% mAP, indicating the suitability of these models to the tag detection problem.
Detection of Graffiti Tags in Image
Fischer, Martin ; Kodym, Oldřich (referee) ; Špaňhel, Jakub (advisor)
The aim of this work is to compare different approaches of computer vision with the intention of automatic detection of graffiti tags in the image. The solution was based on models based on neural networks. Both the proven detection models and the experimental models were tested here. The most accurate one (Faster R-CNN) achieved an accuracy of 83% mAP, indicating the suitability of these models to the tag detection problem.

See also: similar author names
1 Fischer, Marek
2 Fischer, Michael
4 Fischer, Michal
5 Fischer, Milan
2 Fischer, Monika
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