Analysis: Performance Comparison of Various CNN Models on different Datasets

Within the field of image processing, the term "computer vision" is growing in use. There is a big need for automatic object recognition now that computer vision applications are starting to take off. The computer vision community has profited from the convolution neural network (CNN), which has excelled in many disciplines including speech recognition, object categorization, segmentation, video editing, and many more. This manuscript's key contribution is to contrast several architectural evolutions based on architectural development, advantages, and disadvantages. A breakdown of the elements of CNN, advantages, and disadvantages of different variations on CNN, knowledge gaps or unresolved problems, CNN applications, and future research directions are also included. When it comes to machine learning issues, CNN performs superbly. In this essay, we will outline and identify every component of CNN, its key components, and its concerns