A SURVEY ON DEEP LEARNING TECHNIQUES APPLICATIONS AND CHALLENGES

dc.contributor.authorV, Pream Sudha
dc.contributor.authorR, Kowsalya
dc.date.accessioned2020-09-29T06:26:44Z
dc.date.available2020-09-29T06:26:44Z
dc.date.issued2015
dc.description.abstractDeep learning is an emerging research area in machine learning and pattern recognition field. Deep learning refers to machine learning techniques that use supervised or unsupervised strategies to automatically learn hierarchical representations in deep architectures for classification. The objective is to discover more abstract features in the higher levels of the representation, by using neural networks which easily separates the various explanatory factors in the data. In the recent years it has attracted much attention due to its state-of-the-art performance in diverse areas like object perception, speech recognition, computer vision, collaborative filtering and natural language processing. As the data keeps getting bigger, deep learning is coming to play a key role in providing big data predictive analytics solutions. This paper presents a brief overview of deep learning, techniques, current research efforts and the challenges involved in iten_US
dc.identifier.issn2319-8354
dc.identifier.urihttps://www.ijarse.com/images/fullpdf/1428670381_36_Research_Paper.pdf
dc.identifier.urihttps://dspace.psgrkcw.com/handle/123456789/1850
dc.language.isoenen_US
dc.publisherInternational Journal of Advance Research In Science And Engineeringen_US
dc.subjectAuto-Encodersen_US
dc.subjectCNNen_US
dc.subjectDeep learningen_US
dc.subjectRBMen_US
dc.titleA SURVEY ON DEEP LEARNING TECHNIQUES APPLICATIONS AND CHALLENGESen_US
dc.typeArticleen_US

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