Interactive Case-Based Reasoning in Sequential Diagnosis
Applied Intelligence
Supporting Dialogue Inferencing in Conversational Case-Based Reasoning
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
A Fuzzy-Rough Approach for Case Base Maintenance
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Mining knowledge for HEp-2 cell image classification
Artificial Intelligence in Medicine
Watershed Segmentation Via Case-Based Reasoning
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Case-Based Reasoning and the Statistical Challenges
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Watershed segmentation via case-based reasoning
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
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The development of an automatic image classification system is a hard problem since such a system must imitate the visual strategy of a human expert when interpreting the particular image. Usually it is not easy to make this strategy explicit. Rather than describing the visual strategy and the image features human are able to judge the similarity between the objects. This judgement can be the basis for a guideline of the development process. This guideline can help the developer to understand what kind of case description/features are necessary for a sufficient system performance and can give an idea what system performance can be achieved. In the paper we describe a novel strategy which can support a developer in building image classification systems. The development process as well as the elicitation of the case description is similarity-guided. Based on the similarity between the objects the system developer can provide new image features and improve the system performance until a system performance is reached that fits to the experts understanding about the relationship among the different objects.