the basic concepts of convolutional neural networks

Convolutional neural networks (cnn) were the most successful among the various biology-based artificial intelligence. in the 1960s, hubel and wiesel conducted a series of research on the functioning of the vision system in mammals, which ultimately led to the nobel prize. their findings were based on recording neuronal activity in cats brains, which had the greatest impact on current learning models. by anesthetizing the cats, they could keep their eyes steady and study different neuronal activities in their brains by projecting different images in different parts of the screen in front of the cats. the result of these two scientists led to the discovery of the tasks of various brain parts. in this study, the basic concepts of convolutional neural networks are discussed, from the point of view of deep learning.