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RNNCon: Contribution Coverage Testing for Stacked Recurrent Neural Networks
Recurrent Neural Networks (RNNs) are applied in safety-critical fields such as autonomous driving, aircraft collision detection, and smart credit. They are highly susceptible to input perturbations, but little research on RNN-oriented testing techniques has been conducted, leaving a threat to a larg...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10048185/ https://www.ncbi.nlm.nih.gov/pubmed/36981408 http://dx.doi.org/10.3390/e25030520 |