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Lecture Notes in Computer Science
The existing image interpretation systems lack robustness and accuracy. They cannot adapt to changing environmental conditions or to new objects. The application of machine learning to image interpretation is the next logical step. Our proposed approach aims at the development of dedicated machine learning techniques at all levels of image interpretation in a systematic fashion. In this paper we propose a system which uses Case-Based Reasoning (CBR) to optimize image segmentation at the lowdoi:10.1007/3-540-44527-7_41 fatcat:fs2gmhhiq5dv5ieuaio7cnhzq4