Characterization and recognition of handwrittendigits using Julia
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Automatic image and digit recognition is a compu-tationally challenging task for the image processing and patternrecognition, requiring an adequate appreciation of the syntacticand semantic importance of the image for the identification ofthe handwritten digits. Image and Pattern Recognition has beenidentified as one of the driving forces in the research areasbecause of its shifting of different types of applications, suchas safety frameworks, clinical frameworks, diversion, and so on.In this study, for recognition, we implemented a hybrid neuralnetwork model that is capable of recognizing the digit of MNISTdataset and achieved a remarkable result. The proposed neuralmodel network can extract features from the image and recognizethe features in the layer by layer. To expand, it is so importantfor the neural network to recognize how the proposed modelcan work in each layer, how it can generate output, and so on.Besides, it also can recognize the auto-encoding system and thevariational auto-encoding system of the MNIST dataset. Thisstudy will explore those issues that are discussed above, and theexplanation for them, and how this phenomenon can be overcome.
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