This project features an autoencoder model trained to encode, compress, and decode hand-written digits. There are two files, model_functions.py which contains the functions and structure of the model.

Abstract: In image classification, identification of handwritten digits forms a simple choreacle especially with datasets such as MNIST that has grown to become a benchmark for testing machine ...

Abstract: Innovations continue in the field of image processing and image synthesis, as in many other fields, with the advancement of artificial intelligence. With the use of various neural networks ...