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      • Theses - Graduate Program in Neuroscience
      • Graduate Program in Neuroscience - Master's degree
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      The effect of task on cue usefulness for visual scene classification

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      Author(s)
      Karaca, Meltem
      Advisor
      Clarke, Aaron Michael
      Date
      2017-05
      Publisher
      Bilkent University
      Language
      English
      Type
      Thesis
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      Abstract
      Detecting objects in the environment is one of the most fundamental functions of the visual system. Humans are highly effective at this, and past studies have shown that we can process things like whether or not an animal is present in a scene within 150 msec. Different lines of research have also examined possible cues that may be useful for rapid object detection and scene classification, and have found things like color, luminance, shape and texture to be diagnostic. Studies examining the degree to which different cues are effective for detecting objects have found that shape and texture are the most important. However, it is unclear whether cue effectiveness depends on the task being employed. The discriminative information contained in different cues may vary depending on the task. This master’s thesis examines the effects of task-relevant information on which cues are most useful for visual detection. In order to investigate the impact of task type on visual cue usefulness, participants were asked to do animal and water detection tasks. They were presented with natural scenes that contain animals or water. We found significant differences in cue usefulness depending on the task. Corresponding differences were also found for reaction times based on the different cues. The results indicated that effectiveness of visual cues depends on the nature of the task, and different cues might be more or less useful when individuals are instructed to do different kinds of tasks.
      Keywords
      Object recognition
      Scene classification
      Natural scenes
      Signal detection theory
      Visual cues
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      http://hdl.handle.net/11693/33194
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      • Graduate Program in Neuroscience - Master's degree 41
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