Deep Learning Application Pros And Cons Over Algorithm

Ata Jahangir  Moshayedi; Atanu Shuvam  Roy; Amin Kolahdooz; Yang  Shuxin

doi:10.4108/airo.v1i.19

Authors

Ata Jahangir Moshayedi Jiangxi University of Science and Technology
Atanu Shuvam Roy Jiangxi University of Science and Technology
Amin Kolahdooz De Montfort University
Yang Shuxin Jiangxi University of Science and Technology

DOI:

https://doi.org/10.4108/airo.v1i.19

Keywords:

Deep learning, face recognition, speech recognition, medical image recognition, character recognition

Abstract

Deep learning is a new area of machine learning research. Deep learning technology applies the nonlinear and advanced transformation of model abstraction into a large database. The latest development shows that deep learning in various fields and greatly contributed to artificial intelligence so far. This article reviews the contributions and new applications of deep learning. The main target of this review is to give the summarize points for scholars to have the analysis about applications and algorithms. Then review tries to investigate the main applications and uses algorithms. In addition, the advantages of using the method of deep learning and its hierarchical and nonlinear functioning are introduced and compared to traditional algorithms in common applications. The following three criteria should be taken into consideration when choosing the area of application. (1) expertise or knowledge of the author; (2) the successful application of deep learning technology has changed the field of application, such as voice recognition, chat robots, search technology and vision; and (3) deep learning can have a significant impact on the application domain and benefit from recent research with natural language and text processing, information recovery and multimodal information processing resulting from multitasking deep learning. This review provides a general overview of a new concept and the growing benefits and popularity of deep learning, which can help researchers and students interested in deep learning methods.

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