Convolutional Neural Networks

Giriş

Image classification için kullanılabilir. CNN ile "pre-trained" modeller kullanılabilir. Açıklaması şöyle

CNN usually picks up an input which is an image, allot significant features of the image, and then makes the prediction. CNN is much better than the feedforward neural networks due to the way it captivates spatial dependencies from the image. Simply said, CNN understands the image’s composition much better than any other neural network. 

Specifically, CNNs are used to classify images. 

Loss Function

Açıklaması şöyle

The reduction in resolution is a fundamental step in CNN to accelerate processing time

Açıklaması şöyle

 A CNN looks for other features. It tries to minimize a loss function. And the fastest way to do this is often not the intended way. E.g. you think that a cow has like 4 legs and a certain shape of a head. A CNN might think that it is enough if there is something with 4 legs and a green background (because 9 of 10 images in the training dataset are like that). So for most of the cases the CNN does fine when it identifies a cow by these features.