P. Immaculate Rexi Jenifer1,*, S. Kannan2
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1081-1097, 2023, DOI:10.32604/csse.2023.026128
Abstract Medical image classification becomes a vital part of the design of computer aided diagnosis (CAD) models. The conventional CAD models are majorly dependent upon the shapes, colors, and/or textures that are problem oriented and exhibited complementary in medical images. The recently developed deep learning (DL) approaches pave an efficient method of constructing dedicated models for classification problems. But the maximum resolution of medical images and small datasets, DL models are facing the issues of increased computation cost. In this aspect, this paper presents a deep convolutional neural network with hierarchical spiking neural network (DCNN-HSNN) for medical image classification. The proposed… More >
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