This work aims to develop a complete system for image verification Markov networks, were tested with three, one, two, and one hidden layer with two hidden layers. Clothing hidden layer neurons, the hidden layer neurons 25, 50 and 60, respectively, and. All Markov networks were trained for cycles and then compare the rates and include error. It refers to the hidden layer with 50 neutrons, it stands for 60 hidden neurons and Markov networks it refers to the two hidden layers with 25 neurons in each layer.
Recall, Precious, Chain Method, Compressions, Retrieval, Feature, Pattern, Image Processing, Classification
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Mahdi Jalali, "Estimation of Clean Spectrogram Noisy Value Functions Based on Metropolis Iterative Algorithm " Research and Reviews: Journal of Pure and Applied Physics, RRJPAP,Volume 1, Issue 3,July – September, 2013
Tohid Sedghi, Yashar Zeforoosh, Mahdi Jalali, "Response Vector for Calculation of Training Signal based on Progressive Non-Recursive Fusion of Multi-Spectral Image", International Journal of Engineering & Technology Sciences (IJETS) 2 (1): 30-34, 2014
Mahdi Jalali, Tohid Sedghi," Classification Percentage Enhancement of Segmentation Indexed Image based on Clustering Algorithm" International Journal of Engineering & Technology Sciences (IJETS) 2 (1): 1-4, 2014
Mahdi Jalali, “Multi-Scale Recognition of Objects Approach based on Inherent Redundancy Information Entropy Equalization” Research and Reviews: Journal of Engineering and Technology, RRJET, Volume 3, Issue 1, January - March, 2
Mahdi Jalali, "Efficient Color Histogram Relationship Matching Approach Based on Absolute Heavily Dependent Spatial Patterns", International Journal of Engineering & Technology Sciences (IJETS) 1(2): 96-99, 2013
Mahdi Jalali, Mohammad Naser Moghaddasi, Alireza Habibzad, Comparing accuracy for ML, MUSIC, ROOT-MUSIC and spatially smoothed algorithms for 2 users, Microwave Symposium (MMS), 2009 Mediterrannean.