Build a Neural Network for Image Zooming 🖼️

Source Code : https://github.com/Guraku-Black/typelibrary/
#shorts

Zooming into an image is is similar to rotating an image. We just need to compute the location of each pixel in the result image relative to the source pixel. This process is useful when doing data Augmentation for Neural Network training.

Using only the C Programming language and Visual Studio, We are going create a Neural Network that includes, Convolutional Layers, RELU, SIGMOID and TANH Layers, Fully Connected Layers, as well as Dropout Layers.

The basic problem with using programs like TensorFlow or Keras or even the Python language is that they hide a lot of the details of actually running a neural network. It can be hard for example to even find out anything about backpropagation in a Convolutional layer. If you want to really understand what is actually going on in Machine Learning Algorithms, Deep Learning, Computer Vision and Natural Language Processing, or Recurrent Neural Networks, you need to actually know the actual details of the code and not just rely on tools that do most of the work for you.