Convolutional Neural Network and Fuzzy Logic-based Hybrid Melanoma Diagnosis System

Studies on the detection of early stage melanoma have recently gained significant interest. Computer aided diagnosis systems based neural networks, machine learning, convolutional networks (CNNs), and deep learning help considerably. The colour shapes images created by pixels are crucial for CNNs, as associated pictures interrelated just a person’s fingerprint is unique. By observing this relationship, pixel values each picture with its neighborhoods were determined fuzzy logic-based system unique matrix named Fuzzy Correlation Map (FCov-Map) was produced. logic has four inputs one output. advantage CNNs trained covariance maps to eliminate both limited availability medical grade training data need extensive image preprocessing. output fed pretrained AlexNet CNN algorithm. To deliver reliable result, needs large amount process. However, obtain use required sufficient diseases not cost- time-effective. Therefore, suggested correlation map tackling issue solve limitedness set.