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Strengths and weaknesses of deep learning models for face recognition against image degradations

Research article (IET Biometrics, 2017) · cited 215× · AI/ML
academia openalex:W2755255259
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Strengths and weaknesses of deep learning models for face recognition against image degradations

Summary

Strengths and weaknesses of deep learning models for face recognition against image degradations is a scholarly article[1].

Key Facts

  • Strengths and weaknesses of deep learning models for face recognition against image degradations's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Strengths and weaknesses of deep learning models for face recognition against image degradations. Retrieved May 24, 2026, from https://4ort.xyz/entity/strengths-and-weaknesses-of-deep-learning-models-for-face-recognition-against-image-degradations
MLA “Strengths and weaknesses of deep learning models for face recognition against image degradations.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/strengths-and-weaknesses-of-deep-learning-models-for-face-recognition-against-image-degradations.
BibTeX @misc{4ortxyz_strengths-and-weaknesses-of-deep-learning-models-for-face-recognition-against-image-degradations_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Strengths and weaknesses of deep learning models for face recognition against image degradations}}, year = {2026}, url = {https://4ort.xyz/entity/strengths-and-weaknesses-of-deep-learning-models-for-face-recognition-against-image-degradations}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Strengths and weaknesses of deep learning models for face recognition against image degradations — https://4ort.xyz/entity/strengths-and-weaknesses-of-deep-learning-models-for-face-recognition-against-image-degradations (retrieved 2026-05-24)

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