Home > Search Results: recid:387140
Search:
 
Search Tips :: Simple Search
Search collections:
Sort by: Display results: Output format:
National Repository of Grey Literature 1 records found  Search took 0.01 seconds. 

Warning: Requested record does not seem to exist.
Perceptual learning and Ideal Bayesian obsever in visual search task
 Němeček, Viktor ; Děchtěrenko, Filip (advisor) ; Pilát, Martin (referee)
Searching for objects in a complex environment is an activity we do many times each day. Najemnik and Geisler (2005; 2008; 2009) showed in their work that people do not perform optimally, and devised multiple ideal observer models for one particular visual search task. In this thesis we tried to show that if people get feedback from one of the ideal observer models, they learn to solve the task better during a given amount of trials than they would without the feedback. We were unable to prove any nontrivial result with statistical significance due to a small sample size, but the data suggests that the feedback indeed has a positive effect on the learning, and that the continuation of the research is justified. An iOS application necessary for the experiment was created as a part of the thesis. Aside from the experiment itself, one can also use it to play a visual search testing game. 1
Detailed record

Interested in being notified about new results for this query?
Subscribe to the RSS feed.
Digital Repository :: Search :: Submit :: Personalize :: Help
Powered by Invenio v1.1.2
Maintained by admin.invenio@techlib.cz
This site is also available in the following languages:
Česky  English