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  Indian J Med Microbiol
 

Figure 13: The proposed method is compared with spatial clustering[24] (SC), adaptive thresholding[25] (AT), multilevel thresholding[26] (MT), Havrda and Charvat entropy and Otsu N thresholding[73] (HC), cellular neural network[27] (CelNN), wavelet processing and adaptive thresholding[28] (WPAT), dual-stage adaptive thresholding[29] (DuSAT), deep convolutional neural network with support vector machine[40] (DCNN_SVM), convolutional neural networks and a decision scheme[45] (convolutional neural networks + DS), multiscale all convolutional neural Network[50] (M All convolutional neural network) and our proposed method

Figure 13: The proposed method is compared with spatial clustering<sup>[24]</sup> (SC), adaptive thresholding<sup>[25]</sup> (AT), multilevel thresholding<sup>[26]</sup> (MT), Havrda and Charvat entropy and Otsu N thresholding<sup>[73]</sup> (HC), cellular neural network<sup>[27]</sup> (CelNN), wavelet processing and adaptive thresholding<sup>[28]</sup> (WPAT), dual-stage adaptive thresholding<sup>[29]</sup> (DuSAT), deep convolutional neural network with support vector machine<sup>[40]</sup> (DCNN_SVM), convolutional neural networks and a decision scheme<sup>[45]</sup> (convolutional neural networks + DS), multiscale all convolutional neural Network<sup>[50]</sup> (M All convolutional neural network) and our proposed method