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Deep Support Vector Machines for the Identification of Stress Condition from Electrodermal Activity

Research article (International Journal of Neural Systems, 2020) · cited 49× · AI/ML
academia openalex:W3033013105
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Deep Support Vector Machines for the Identification of Stress Condition from Electrodermal Activity

Summary

Deep Support Vector Machines for the Identification of Stress Condition from Electrodermal Activity is a scholarly article[1].

Key Facts

  • Deep Support Vector Machines for the Identification of Stress Condition from Electrodermal Activity's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Deep Support Vector Machines for the Identification of Stress Condition from Electrodermal Activity. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-support-vector-machines-for-the-identification-of-stress-condition-from-electrodermal-activity
MLA “Deep Support Vector Machines for the Identification of Stress Condition from Electrodermal Activity.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-support-vector-machines-for-the-identification-of-stress-condition-from-electrodermal-activity.
BibTeX @misc{4ortxyz_deep-support-vector-machines-for-the-identification-of-stress-condition-from-electrodermal-activity_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep Support Vector Machines for the Identification of Stress Condition from Electrodermal Activity}}, year = {2026}, url = {https://4ort.xyz/entity/deep-support-vector-machines-for-the-identification-of-stress-condition-from-electrodermal-activity}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep Support Vector Machines for the Identification of Stress Condition from Electrodermal Activity — https://4ort.xyz/entity/deep-support-vector-machines-for-the-identification-of-stress-condition-from-electrodermal-activity (retrieved 2026-05-24)

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