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@article{154621,
        author = {Roshani Deepak Pendhari and Dr.V.L Agrawal},
        title = {A Computational Intelligence Based Classification of Endoscopic Tympanic Membrane Images},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {11},
        pages = {725-729},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154621},
        abstract = {In this paper classification Endoscopic Tympanic Membrane Images , which uses the WHT  transform over the Tympanic Membrane images as feature detector and a constructive one hidden layer Multilayer perceptron  neural network as classification Tympanic Membrane Images classifier  technique is applied to a database consisting of images of 115 having endoscopic Tympanic Membrane Images. It is demonstrated that the best  recognition  rates  are 97.29%. Finally, optimal algorithm has been developed on the basis of the best classifier performance.  The Genetic algorithm will provide an effective alternative method of Classification endoscopic Tympanic Membrane using Neural Network Approach.},
        keywords = {Neural network, Microsoft excel, MatLab, Endoscopic Tympanic Membrane Images.},
        month = {},
        }