How do you determine what convolutional layers look for in Tensorflow?

Question

This is my first post, so I'm sorry if I'm doing something wrong. I'm a beginner when it comes to machine learning. I want to create an accurate model with the cifar10 dataset. I've learned that a Conv2D layer looks for a specific thing in an image classification model. But how do I know what the layer is looking for? I'm not sure if I make sense here, or if anything I've learned so far is true could someone help me out in understanding how layers work in tensorfow?

Answer 1

Convolutional layers extract features from images. They apply a filter to images and output a feature map. Then, one may add dense layers afterwards to obtain labels from these features.

Conv2D is just a 2d convolution used with 2d images - this means that the kernel is 2d also.

Here are a few helpful links: https://machinelearningmastery.com/convolutional-layers-for-deep-learning-neural-networks/

https://towardsdatascience.com/simple-introduction-to-convolutional-neural-networks-cdf8d3077bac