Feb. 16, 2022, 2:20 a.m. | Haibo Jin, Ruoxi Chen, Haibin Zheng, Jinyin Chen, Zhenguang Liu, Qi Xuan, Yue Yu, Yao Cheng

cs.CR updates on arXiv.org arxiv.org

Despite impressive capabilities and outstanding performance, deep neural
network(DNN) has captured increasing public concern for its security problem,
due to frequent occurrence of erroneous behaviors. Therefore, it is necessary
to conduct systematically testing before its deployment to real-world
applications. Existing testing methods have provided fine-grained criteria
based on neuron coverage and reached high exploratory degree of testing. But
there is still a gap between the neuron coverage and model's robustness
evaluation. To bridge the gap, we observed that neurons which …

deep learning framework lg testing

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