Introduction to Convolutional Neural Networks CNNs
Artificial Intelligence or, in short, AI is seeing a massive advancement in narrowing the gap between machines and humans. Researchers and practitioners all around the world have been working on various aspects of AI to develop epic procedures for this purpose. Computer vision is one of the domains of this field. The main aim of computer vision is to make the machines view the world just like humans do and use the knowledge for a wide number of activities, including image recognition, video recognition, Imagery analysis and classification, recommendation systems, and many more. Massive progress is seen in computer vision by a very specific algorithm called the Convolutional Neural Network CNN. CNN has been structured based on the Deep learning method of machine learning.
Introduction:
The convolutional Neural Network CNN works by getting an image, designating it some weightage based on the different objects of the image, and then distinguishing them from each other. CNN requires very little pre-process data as compared to other deep learning algorithms. One of the main capabilities of CNN is that it applies primitive methods for training its classifiers, which makes it good enough to learn the characteristics of the target object.
