A Review of Deep Learning and a Discussion of its Potential Advancements
Abstract
This paper is a summary of the algorithms for deep learning and a brief discussion of its future development. In the first part, the concept of deep learning and the advantages and disadvantages of deep learning are introduced. The second part demonstrates several algorithms for deep learning. As early as 1952, IBM's Arthur Samuel designed a program for learning checkers. It can build new models by observing the moves of the pieces and use them to improve their playing skills. In 1959, the concept of machine learning was proposed as a field of study that could give a machine a certain skill without the need for deterministic programming. In the process of machine learning development, various machine learning models have been proposed, including deep learning. Due to its complicated structure and the need for a large amount of calculation, the computing cost is very high, so it had not been paid attention to at the beginning. However, with the great improvement in computer performance, the excellent performance of deep learning makes it rose rapidly and has become one of the hottest research areas. The third part introduces the application areas of deep learning. Then combines the above algorithms and applications to explore the subsequent development of deep learning. The last part makes a summary of the full paper
Keywords
Sign Language Recognition, Convolution Neural Network, Image Processing.