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Automatic image and digit recognition is a computationally challenging taskfor image processing and pattern recognition, requiring an adequateappreciation of the syntactic and semantic importance of the image for theidentification ofthe handwritten digits. Image and Pattern Recognition has beenidentified as one of the driving forces in the research areas because of itsshifting of different types of applications, such as safety frameworks,clinical frameworks, diversion, and so on.In this study, for recognition, weimplemented a hybrid neural network model that is capable of recognizing thedigit of MNISTdataset and achieved a remarkable result. The proposed neuralmodel network can extract features from the image and recognize the features inthe layer by layer. To expand, it is so important for the neural network torecognize how the proposed modelcan work in each layer, how it can generateoutput, and so on. Besides, it also can recognize the auto-encoding system andthe variational auto-encoding system of the MNIST dataset. This study willexplore those issues that are discussed above, and the explanation for them,and how this phenomenon can be overcome.

Characterization and recognition of handwritten digits using Julia