I’ve only found this page about a week ago, so I don’t have public projects using fuzzylite yet, however, I’d like to encourage every reader to use fuzzy logic in their area of interest, if possible.
I’m currently a PhD student and my area of interest is image processing, feature extraction, pattern and object recognition and classification. I just made some experiments using a Fuzzy Inference System (FIS) for a feature extraction task, and preliminary results are very promising. I wouldn’t like to go into details as long as a publication of the task is not assembled and reviewed in a conference, however, I’d like to tell FIS seems to be efficient so far. There are many humanly observeable features of object or textures in the image domain that can be expressed using fuzzy membership functions, and rule-based decisions are perfectly suitable for classification of images or image parts.
Juan: I’d also like to ask a question, since I’ve read in your CV that you are an expert of AI. Have you ever used/thought about using neuro-fuzzy implementations, or any hybrid solutions where a FIS is not only designed by human knowledge base, but they are reinforced by machine learning? The strength of rules and the parameters of membership functions can be optimized, maybe even the number and shape of memberships and the rules themselves. So my question is, have you ever worked with hybrid solutions like that? If so, please let me know by giving literature or anything about how ML and FIS can be efficiently bound together. Thank you in advance.