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Attention Aware Deep Learning Approaches for an Efficient Stress Classification Model

Attention Aware Deep Learning Approaches for an Efficient Stress Classification Model

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1519517296b34aecaec5161502116ebd

Attention Aware Deep Learning Approaches for an Efficient Stress Classification Model

About this item

Full title

Attention Aware Deep Learning Approaches for an Efficient Stress Classification Model

Publisher

Switzerland: MDPI AG

Journal title

Brain sciences, 2023-06, Vol.13 (7), p.994

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

In today's world, stress is a major factor for various diseases in modern societies which affects the day-to-day activities of human beings. The measurement of stress is a contributing factor for governments and societies that impacts the quality of daily lives. The strategy of stress monitoring systems requires an accurate stress classification te...

Alternative Titles

Full title

Attention Aware Deep Learning Approaches for an Efficient Stress Classification Model

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_1519517296b34aecaec5161502116ebd

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1519517296b34aecaec5161502116ebd

Other Identifiers

ISSN

2076-3425

E-ISSN

2076-3425

DOI

10.3390/brainsci13070994

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