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The Understanding of Deep Learning: A Comprehensive Review

Ranjan Kumar Mishra, G. Y. Sandesh Reddy, Himanshu Pathak

2021Mathematical Problems in Engineering80 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Deep learningComputer scienceArtificial intelligenceAbstractionCognitive neuroscience of visual object recognitionRepresentation (politics)Face (sociological concept)Artificial neural networkFacial recognition systemMachine learningObject (grammar)Data scienceHuman–computer interactionPattern recognition (psychology)PoliticsLawSociologyEpistemologyPolitical scienceSocial sciencePhilosophyAdvanced Neural Network ApplicationsGenerative Adversarial Networks and Image SynthesisFace recognition and analysis
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