What is Image Classification? An Overview
Article n°4 of the “Deep Learning for Computer Vision” series
Image classification is a topic of pattern recognition part of the computer vision domain. It aims to reduce the semantic gap, which is the difference between how a human perceives the contents of an image versus how an image can be represented in the way a computer can understand its content.
In other words, image classification takes as input an image and output a class (e.g. a cat, a dog, …) or a probability of classes that best describes the content of the image. An example of this task and its output is given below.
This task is not as easy because several challenges are faced when processing images in computer vision, e.g. viewpoint variation, scale variation, deformation, occlusions, illumination, background chatter, and interclass variation …
In Deep Learning; the image classification is done in four steps. First, you gather the data and annotate it…
