TEASMA

Replication package of TEASMA: A Practical Methodology for Test Adequacy Assessment of Deep Neural Networks<br>

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.26183348
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
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TEASMA

Figshare
Adversarial Robustness in Machine Learning
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TEASMA

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Abstract

Replication package of TEASMA: A Practical Methodology for Test Adequacy Assessment of Deep Neural Networks<br>

Figshare
Reduced inequalities
Openalex Percentile: Top 74%
Adversarial Robustness in Machine Learning
DOIOpen Access PDFOpenAlex
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TEASMA · Figshare (2025) | TGRS Research Map | TGRS