Comparative Analysis of Feature Extraction Capabilities between Machine and Human in Visual Pattern Recognition Tasks Utilizing a Pattern Classification Framework

نویسندگان

  • Amir Schur
  • Sung-Hyuk Cha
  • Charles C. Tappert
چکیده

There have been many recent advances in pattern recognition technologies, particularly those involving visual pattern recognition tasks. How do these machine capabilities compare to human capabilities in visual pattern recognition tasks? Which can perform better in the feature extraction processes, machine or human? This study compares machine and human in color and shape recognition tasks, as part of a visual pattern recognition system. A pattern classification framework will be used to provide a foundation for understanding where this work fits in context with other work. This is a work in progress for a dissertation by the first author. Keywords—pattern recognition, feature extraction, human and

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تاریخ انتشار 2013