Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
A case-based apprentice that learns from fuzzy examples
Methodologies for intelligent systems, 5
Advances in fuzzy integration for pattern recognition
Fuzzy Sets and Systems - Special issue on fuzzy methods for computer vision and pattern recognition
Face to interface: facial affect in (hu)man and machine
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Automatic Analysis of Facial Expressions: The State of the Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Case-Based Learning of Strategic Knowledge
EWSL '91 Proceedings of the European Working Session on Machine Learning
Similarity Measures for Case-Based Reasoning Systems
IPMU '92 Proceedings of the 4th International Conference on Processing and Management of Uncertainty in Knowledge-Based Systems: Advanced Methods in Artificial Intelligence
A Two Layer Case-Based Reasoning Architecture for Medical Image Understanding
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
Case-Based Classification of Ultrasonic B-Scans: Case-Base Organisation and Case Retrieval
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
MacRad: Radiology Image Resource with a Case-Based Retrieval System
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
CGIV '04 Proceedings of the International Conference on Computer Graphics, Imaging and Visualization
Recognizing Facial Expression: Machine Learning and Application to Spontaneous Behavior
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
The Knowledge Engineering Review
Image processing in case-based reasoning
The Knowledge Engineering Review
Computer-Aided Diagnosis of Intracranial Aneurysms in MRA Images with Case-Based Reasoning
IEICE - Transactions on Information and Systems
Fuzzy Rule Based Facial Expression Recognition
CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce
CBR: fuzzified case retrieval approach for facial expression recognition
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Capturing and reusing case-based context for image retrieval
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Intelligent Expression Blending for Performance Driven Facial Animation
IEEE Transactions on Consumer Electronics
Knowledge and intelligent computing system in medicine
Computers in Biology and Medicine
Combinations of case-based reasoning with other intelligent methods
International Journal of Hybrid Intelligent Systems - CIMA-08
Expert Systems with Applications: An International Journal
An integrated case-based reasoning and MCDM system for Web based tourism destination planning
Expert Systems with Applications: An International Journal
Introducing attribute risk for retrieval in case-based reasoning
Knowledge-Based Systems
Engineering Applications of Artificial Intelligence
Expert Systems with Applications: An International Journal
Facial expression feature selection based on rough set
ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
Bee royalty offspring algorithm for improvement of facial expressions classification model
International Journal of Bio-Inspired Computation
An intelligent route management system for electric vehicle charging
Integrated Computer-Aided Engineering
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Fuzzy logic (FL) and case-based reasoning (CBR) are two well-known techniques for the implementation of intelligent classification systems. Each technique has its own advantages and drawbacks. FL, for example, provides an intuitive user interface, simplifies the process of knowledge representation, and minimizes the system's computational complexity in terms of time and memory usage. On the other hand, FL has problems in knowledge elicitation which render it difficult to adopt for intelligent system implementation. CBR avoids these problems by making use of past input-output data to decide the system output for the present input. The accuracy of CBR system grows as the number of cases increase. However, more cases can mean added computational complexity in terms of space and time. In this paper we make the proposition that a hybrid system comprising a blend of FL and CBR can lead to a solution where the two approaches cover each other's weaknesses and benefit from each other's strengths. We support our claim by taking the problem of facial expression recognition from an input image. The facial expression recognition system presented in this paper uses a case base populated with fuzzy rules for recognizing each expression. Experimental results demonstrate that the system inherits the strengths of both methods.