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Knowledge Transfer in Semi-automatic Image Interpretation (2008)

Abstract
Abstract. Semi-automatic image interpretation systems utilize interactions between users and computers to adapt and update interpretation algorithms. We have studied the influence of human inputs on image interpretation by examining several knowledge transfer models. Experimental results show that the quality of the system performance depended not only on the knowledge transfer patterns but also on the user input, indicating how important it is to develop user-adapted image interpretation systems.

Publication details
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.92.492
Source http://www.cs.ualberta.ca/~jzhou/papers/C_HCII_2007.pdf
Contributors CiteSeerX
Repository CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Keywords knowledge transfer, image interpretation, road tracking, human influence, performance
Type text
Language English
Relation 10.1.1.106.8339, 10.1.1.45.9491, 10.1.1.134.9962