By Ralph Bergmann (auth.), David W. Aha, Ian Watson (eds.)
The 2001 overseas convention on Case-Based Reasoning (ICCBR 2001, www.iccbr.org/iccbr01), the fourth within the biennial ICCBR sequence (1995 in Sesimbra, Portugal; 1997 in windfall, Rhode Island (USA); 1999 in Seeon, Germany), was once held in the course of 30 July – 2 August 2001 in Vancouver, Canada. ICCBR is the top-rated overseas discussion board for researchers and practitioners of case dependent reasoning (CBR). The pursuits of this assembly have been to nurture major, suitable advances made during this box (both in study and application), converse them between all attendees, encourage destiny advances, and proceed to aid the imaginative and prescient that CBR is a helpful technique in lots of examine disciplines, either computational and differently. ICCBR 2001 used to be the 1st ICCBR assembly hung on the Pacific coast, and we used the environment of lovely Vancouver as a chance to reinforce participation from the Pacific Rim groups, which contributed 28% of the submissions. in this assembly, we have been lucky to host invited talks via Ralph Bergmann, Ken Forbus, Jaiwei Han, Ramon López de Mántaras, and Manuela Veloso. Their contributions ensured a stimulating assembly; we thank them all.
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Additional info for Case-Based Reasoning Research and Development: 4th International Conference on Case-Based Reasoning, ICCBR 2001 Vancouver, BC, Canada, July 30 – August 2, 2001 Proceedings
Why Case-Based Reasoning Is Attractive for Image Interpretation Petra Perner Institute of Computer Vision and Applied Computer Sciences Arno-Nitzsche-Str. de Abstract. The development of image interpretation systems is concerned with tricky problems such as a limited number of observations, environmental influence, and noise. Recent systems lack robustness, accuracy, and flexibility. The introduction of case-based reasoning (CBR) strategies can help to overcome these drawbacks. , images) and the problems mentioned above provide special requirements for CBR strategies.
Grimnes, M. (1996). A two layer case-based reasoning architecture for medical image understanding, In I. Smith & B. ) Advances in Case-Based Reasoning (pp. 164-178). Berlin: Springer Verlag. Perner, P. (1999). An architecture for a CBR image segmentation system. Journal of Engineering Application in Artificial Intelligence, 12(6), 749-759. Micarelli, A. , & Sansonetti, G. (2000). A case-based approach to image recognition, In E. Blanzieri & L. ) Advances in Case-Based Reasoning (pp. 443-454). Berlin: Springer Verlag.
The user can interact with SaxEx in the four main CBR subtasks. This new functionality requires that the use and combination of the two basic mechanisms—perspectives and preferences— in the Retrieve and Reuse subtasks must be parameterizable and dynamically modifiable. 3 Retrieval Perspectives Retrieval perspectives  are built by the identify subtask and can be used either by the search or the select subtask. Perspectives used by the search subtask will act as filters. Perspectives used by the select subtask will act only as a preference.
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