Design of a hierarchical fuzzy filter for removal of heavy impulse noise from corrupted images
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Summary
It is shown how evolutionary algorithms (EAs) can be used to learn the fuzzy rules in a fuzzy image filter as opposed to determining the rules using human intuition.
- Type
- article
- Published
- 2002-12-02
- Cited by
- 8
- References
- 8
- Access
- Open access
- OpenAlex
- https://openalex.org/W1594561879
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:28601734
Keywords
Fuzzy logic, Intuition, Artificial intelligence, Filter (signal processing), Computer science
References
- Hierarchical fuzzy control
- Adaptive hierarchical fuzzy controller
- Linguistic modeling by hierarchical systems of linguistic rules
- An effective fuzzy image filter
- Idea Grou p Inc . Copy right Idea Grou p Inc . Copy right Idea Grou p Inc . Copy right Idea Grou p Inc . Chapter V Evolutionary Learning of Fuzzy Control in Robot-Soccer
Cited by
- Parameter optimization and rule base selection for fuzzy impulse filters using evolutionary algorithms
- Optimisation of client trust by evolutionary learning of financial planning strategies in an agent based model
- Co-evolutionary learning and hierarchical fuzzy control for the inverted pendulum
- A coevolutionary approach for optimization of image enhancement filters
- Trust as an emergent phenomenon in wealth management relationships
- Hierarchical fuzzy control in robot soccer using evolving algorithms
- Modelling, Control and Prediction using Hierarchical Fuzzy Logic Systems: Design and Development
- Optimization of Fuzzy Impulse Filters using Evolutionary Algorithms
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