Survey on Neural Network Architectures with Deep Learning
Author(s) -
S. Smys,
Joy Iong Zong Chen,
Subarna Shakya
Publication year - 2020
Publication title -
journal of soft computing paradigm
Language(s) - English
Resource type - Journals
ISSN - 2582-2640
DOI - 10.36548/jscp.2020.3.007
Subject(s) - deep learning , artificial intelligence , computer science , machine learning , deep neural networks , artificial neural network , unsupervised learning
In the present research era, machine learning is an important and unavoidable zone where it provides better solutions to various domains. In particular deep learning is one of the cost efficient, effective supervised learning model, which can be applied to various complicated issues. Since deep learning has various illustrative features and it doesn’t depend on any limited learning methods which helps to obtain better solutions. As deep learning has significant performance and advancements it is widely used in various applications like image classification, face recognition, visual recognition, language processing, speech recognition, object detection and various science, business analysis, etc., This survey work mainly provides an insight about deep learning through an intensive analysis of deep learning architectures and its characteristics along with its limitations. Also, this research work analyses recent trends in deep learning through various literatures to explore the present evolution in deep learning models.
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