Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/111
Title: TCDR based on Efficiency and Accuracy of the Intelligent Systems
Authors: Abdulbaqi, Azmi
Mosslah, Abd
Mahdi, Reyadh
Keywords: Radial Bases Function (RBF) neural network
MultiLayer Perceptron (MLP)
Feature Extraction
Genetic Algorithm (GA)
Canny Edge Detection (CED).
Issue Date: 2016
Publisher: University Sultan Moulay Suleiman
Abstract: :According the recent world health organization (WHO) reports, one person every hour of every day dies of oral cancer in the united states. Oral cancer is a term used to describe any tumor appears in the oral cavity. The origin of the tumor may be a prototype of the oral tissues or may be a minor mouth tumor. Tongue cancer is one of oral diseases and it’s a common disease. In this paper, tongue cancer detection and recognition (TCDR) system using Radial Bases Function (RBF) Neural Network, MultiLayer Perceptron (MLP) and Genetic algorithm (GA) is proposed. The proposed system consists of mainly three steps: first, pre-processing are applied to the input image (Mouth image, gum image and tongue image). Second, extracted the features of tumor tissue. This feature is being as input parameters to the hybrid algorithm. The final step, the proposed algorithm is implement the classification to acquire the results.
URI: https://acit2k.org/ACIT/images/stories/year2014/month1/proceeding/53_Paper__ID-.pdf
http://localhost:8080/xmlui/handle/123456789/111
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