Exposing previously undetectable faults in deep neural networks
Existing methods for testing DNNs solve the oracle problem by constraining the raw features (e.g. image pixel values) to be within a small distance of a dataset example for which the desired DNN output is known. But this limits the kinds of faults these approaches are able to detect. In this paper,...
| Main Authors: | , , , |
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| 格式: | Conference item |
| 語言: | English |
| 出版: |
Association for Computing Machinery
2021
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