The Understanding of Deep Learning: A Comprehensive Review
Author(s) -
Ranjan Mishra,
G. Y. Sandesh Reddy,
Himanshu Pathak
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/5548884
Subject(s) - deep learning , computer science , artificial intelligence , abstraction , cognitive neuroscience of visual object recognition , representation (politics) , face (sociological concept) , artificial neural network , facial recognition system , machine learning , object (grammar) , data science , human–computer interaction , pattern recognition (psychology) , social science , philosophy , epistemology , politics , sociology , political science , law
Deep learning is a computer-based modeling approach, which is made up of many processing layers that are used to understand the representation of data with several levels of abstraction. This review paper presents the state of the art in deep learning to highlight the major challenges and contributions in computer vision. This work mainly gives an overview of the current understanding of deep learning and their approaches in solving traditional artificial intelligence problems. These computational models enhanced its application in object detection, visual object recognition, speech recognition, face recognition, vision for driverless cars, virtual assistants, and many other fields such as genomics and drug discovery. Finally, this paper also showcases the current developments and challenges in training deep neural network.
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