Testing coverage criteria for optimized deep belief network with search and rescue

Testing coverage criteria for optimized deep belief network with search and rescue

Abstract A new data-driven programming model is defined by the deep learning (DL) that makes the internal structure of a created neuron system over a fixed of training data. DL testing structure only depends on the data labeling and manual group. Nowadays, a lot of coverage criteria have been develo...

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Bibliographic Details
Main Authors: Kiran Jammalamadaka, Nikhat Parveen
Format: Article
Language:English
Published: SpringerOpen 2021-04-01
Series:Journal of Big Data
Subjects:
Deep learning
Coverage criteria
Optimization algorithm
Adversarial example
Software testing
Online Access:https://doi.org/10.1186/s40537-021-00453-7

Internet

https://doi.org/10.1186/s40537-021-00453-7

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