Question: Fuzzy Sets and Membership Functions: Define fuzzy sets for concavity and shape, each with appropriate membership functions. Consider the nuances in the images and
Fuzzy Sets and Membership Functions: Define fuzzy sets for concavity and shape, each with appropriate membership functions. Consider the nuances in the images and aim for a representation that captures the complexities of these features. Rules: Develop a set of rules that correlate concavity and shape features to CVM stages. Leverage engineering intuition to create rules that reflect the relationships observed in the x-ray images. Fuzzy Inference System: Implement a fuzzy inference system using a suitable defuzzification method. Consider how the rules combine to predict the CVM stage based on the input features. Validation and Testing: Validate your fuzzy logic model using additional x-ray images not provided in the homework. Analyze the accuracy of your model in predicting CVM stages compared to the ground truth. Fuzzy Sets and Membership Functions: Define fuzzy sets for concavity and shape, each with appropriate membership functions. Consider the nuances in the images and aim for a representation that captures the complexities of these features. Rules: Develop a set of rules that correlate concavity and shape features to CVM stages. Leverage engineering intuition to create rules that reflect the relationships observed in the x-ray images. Fuzzy Inference System: Implement a fuzzy inference system using a suitable defuzzification method. Consider how the rules combine to predict the CVM stage based on the input features. Validation and Testing: Validate your fuzzy logic model using additional x-ray images not provided in the homework. Analyze the accuracy of your model in predicting CVM stages compared to the ground truth.
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The question you presented pertains to the design and implementation of a fuzzy logic model to analyze xray images focusing particularly on features such as concavity and shape to predict cervical ver... View full answer
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