  Automatic image and digit recognition is a computationally challenging task
for image processing and pattern recognition, requiring an adequate
appreciation of the syntactic and semantic importance of the image for the
identification ofthe handwritten digits. Image and Pattern Recognition has been
identified as one of the driving forces in the research areas because of its
shifting of different types of applications, such as safety frameworks,
clinical frameworks, diversion, and so on.In this study, for recognition, we
implemented a hybrid neural network model that is capable of recognizing the
digit of MNISTdataset and achieved a remarkable result. The proposed neural
model network can extract features from the image and recognize the features in
the layer by layer. To expand, it is so important for 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
the variational auto-encoding system of the MNIST dataset. This study will
explore those issues that are discussed above, and the explanation for them,
and how this phenomenon can be overcome.
