Abstract
This study investigates methods of enhancing human-computer interaction in applications of visual pattern recognition where higher accuracy is required than is currently achievable by automated systems, but where there is enough time for a limited amount of human interaction. The first author’s doctoral dissertation research and experiments are summarized here. Within this study the following questions are explored: How do machine capabilities compare to human capabilities in visual pattern recognition tasks in terms of accuracy and speed? Can we improve machine-only accuracy in visual pattern recognition tasks? Should we employ human assistance in the feature extraction process? Finally, human assistance is explored in color and shape/contour recognition within a machine visual pattern recognition framework.
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Schur, A.I., Tappert, C.C. (2017). Speed and Accuracy Improvements in Visual Pattern Recognition Tasks by Employing Human Assistance. In: Nunes, I. (eds) Advances in Human Factors and System Interactions. Advances in Intelligent Systems and Computing, vol 497. Springer, Cham. https://doi.org/10.1007/978-3-319-41956-5_26
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DOI: https://doi.org/10.1007/978-3-319-41956-5_26
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