Detection of dynamic Gabor patches in 1/f noise
Detekce dynamických Gaborových vlnek v 1/f šumu
diploma thesis (DEFENDED)

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http://hdl.handle.net/20.500.11956/124658Identifiers
Study Information System: 222986
CU Caralogue: 990024256350106986
Collections
- Kvalifikační práce [11342]
Author
Advisor
Referee
Pilát, Martin
Faculty / Institute
Faculty of Mathematics and Physics
Discipline
Artificial Intelligence
Department
Department of Software and Computer Science Education
Date of defense
4. 2. 2021
Publisher
Univerzita Karlova, Matematicko-fyzikální fakultaLanguage
English
Grade
Excellent
Keywords (Czech)
detection|modeling|1, f noise|Gabor patchKeywords (English)
detection|modeling|1, f noise|Gabor patchResearch focusing on static scenes with static objects is omitting the time factor from real life examples we are trying to study. Can we say that a lifeguard looking for a drowning man is using the same brain processes that were observed in the laboratory for static scenes? We can conclude that a static scene is a big simplification of the task itself. The aim of this thesis is to prepare a tool which would allow researching dynamic scenes and thus broadening the possibilities of visual detection tasks at hand. Along the tool we also present a couple of simplified examples with which we would like to demonstrate the utilization of the tool. All concluding with a final experiment in which we will try to detect masked patterns in a noisy environment. 1
Research focusing on static scenes with static objects is omitting the time factor from real life examples we are trying to study. Can we say that a lifeguard looking for a drowning man is using the same brain processes that were observed in the laboratory for static scenes? We can conclude that a static scene is a big simplification of the task itself. The aim of this thesis is to prepare a tool which would allow researching dynamic scenes and thus broadening the possibilities of visual detection tasks at hand. Along the tool we also present a couple of simplified examples with which we would like to demonstrate the utilization of the tool. All concluding with a final experiment in which we will try to detect masked patterns in a noisy environment. 1