title: How does a neural network work with correlated image data
body: <p>I am new to TensorFlow and deep learning.  I am trying to create a fully connected neural network for image processing. I am somewhat confused.</p>
  
  <p>We have an image, say 28x28 pixels.  This will have 784 inputs to the NN. For non-correlated inputs, this is fine, but image pixels are generally correlated. For instance, consider a picture of a cow's eye.  How can a neural network understand this when we have all pixels lined up in an array for a fully-connected network.  How does it determine the correlation?</p>