Name
Abstract | ||
|---|---|---|
Recently, there has been a significant growth of interest in applying software engineering techniques for the quality assurance of deep learning (DL) systems. One popular direction is deep learning testing, where adversarial examples (a.k. a. bugs) of DL systems are found either by fuzzing or guided search with the help of certain testing metrics. However, recent studies have revealed that the com... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICSE43902.2021.00038 | 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) |
Keywords | DocType | ISSN |
Measurement,Deep learning,Benchmark testing,Robustness,Robots,Software engineering,Convergence | Conference | 0270-5257 |
ISBN | Citations | PageRank |
978-1-6654-0296-5 | 1 | 0.36 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| wang jingyi | 1 | 72 | 16.19 |
| Jialuo Chen | 2 | 1 | 0.70 |
| Youcheng Sun | 3 | 130 | 12.18 |
| Xingjun Ma | 4 | 1 | 1.37 |
| Dongxia Wang | 5 | 1 | 0.36 |
| Jun Sun | 6 | 1407 | 120.35 |
| Peng Cheng | 7 | 1481 | 85.79 |