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Pattern Recognition, Medical Imaging, Machine Intelligence, Computer Vision Hamid R. Tizhoosh
Faculty of Engineering
University of Waterloo

Pattern Recognition, Computer Vision,
Medical Imaging, Machine Intelligence		 Hamid R. Tizhoosh
Teaching
Computer Vision
Machine Intelligence
Data Structures
SD750 - OBL
Research
Pattern Recoginition
Computer Vision
Machine Intelligence
Terahertz Imaging
Health Engineering
Opposition-Based Learning
Students
Current Students
Former Students
Projects
LORNET
Prostate Cancer
Breast Cancer
Radiation Therapy
Other Projects
Publications
Books & Chapters
Journals
Conferences
Reports etc.
University of Waterloo :: Faculty of Engineering :: Systems Design

Research …
Fuzzy Logic

Fuzzy logic is the extension of the dual or multivalued set theory. It deals with mathematical modeling of vague concepts. Popular fuzzy techniques include (type I) fuzzy inference systems and fuzzy clustering.

Fuzzy Logic

Fields

  • Type II Fuzzy Sets

  • Type II Inference

  • Possibility Theory

  • Fuzzy & Rough Sets

  • Fuzzy Measures & Integrals

  • Fuzzy Morphology

Applications

More Information

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The Type II World

Type I, or regular fuzzy sets, are mathematical tools to model vagueness and imprecision. The uncertainty, however, cannot be captured by fuzzy sets (or subsets).

Type I versus Type II Fuzzy Sets

Type II fuzzy sets, or two dimensional fuzzy sets are able to deal with both vagueness and uncertainty.


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