Knowledge Transfer in Semi-automatic Image Interpretation
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.
|Collections||ANU Research Publications|
|Source:||Proceedings of Human-Computer Interaction International 2007|
|01_Zhou_Knowledge_Transfer_in_2007.pdf||198.05 kB||Adobe PDF||Request a copy|
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