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Over the past decades, deep learning (DL) systems have achieved tremendous success and gained great popularity in various applications, such as intelligent machines, image processing, speech processing, and medical diagnostics.
Pressman, R.: Software Engineering: A Practitioner’s Approach. McGraw-Hill, Inc., New York, NY, USA, 7 edn. (2010)
2010
Earlier work this paper cites.
Ruparelia, N.B.: Software development lifecycle models. SIGSOFT Softw. Eng. Notes 35
2010
Earlier work this paper cites.
Biggio, B., Corona, I., Maiorca, D., Nelson, B., Šrndić, N., Laskov, P., Giacinto, G., Roli, F.: Evasion attacks against machine learning at test time. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases. pp. 387–402. Springer (2013)
2013
Earlier work this paper cites.
Chen, C., Seff, A., Kornhauser, A., Xiao, J.: Deepdriving: Learning affordance for direct perception in autonomous driving. In: 2015 IEEE International Conference on Computer Vision (ICCV). pp. 2722–2730 (Dec 2015). https://doi.org/10.1109/ICCV.2015.312
2015
Earlier work this paper cites.
Goodfellow, I.J., Shlens, J., Szegedy, C.: Explaining and harnessing adversarial examples. ICLR (2015)
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
BBC: Google’s DeepMind to peek at NHS eye scans for disease analysis (2016), https://www.bbc.com/news/technology-36713308
2016
Earlier work this paper cites.
Google Accident: A Google self-driving car caused a crash for the first time (2016), https://www.theverge.com/2016/2/29/11134344/google-self-driving-car-crash-report
2016
Earlier work this paper cites.
Lipton, Z.C.: The mythos of model interpretability. CoRR abs/1606.03490
2016
Earlier work this paper cites.
Papernot, N., McDaniel, P., Jha, S., Fredrikson, M., Celik, Z.B., Swami, A.: The limitations of deep learning in adversarial settings. In: Security and Privacy (EuroS&P), 2016 IEEE European Symposium on. pp. 372–387. IEEE (2016)
2016
Earlier work this paper cites.
Papernot, N., McDaniel, P.D., Wu, X., Jha, S., Swami, A.: Distillation as a defense to adversarial perturbations against deep neural networks. In: IEEE Symposium on Security and Privacy, SP 2016. pp. 582–597 (2016)
2016
Earlier work this paper cites.
Xiang, Y., Kim, W., Chen, W., Ji, J., Choy, C., Su, H., Mottaghi, R., Guibas, L., Savarese, S.: Objectnet3d: A large scale database for 3d object recognition. In: European Conference Computer Vision (ECCV) (2016)
2016
Earlier work this paper cites.
Xu, W., Qi, Y., Evans, D.: Automatically evading classifiers. In: Proceedings of the 2016 Network and Distributed Systems Symposium (2016)
2016
Earlier work this paper cites.
Carlini, N., Wagner, D.: Towards evaluating the robustness of neural networks. In: Security and Privacy (SP), IEEE Symposium on. pp. 39–57 (2017)
2017
Cited alongside, same era.
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Eliot, L.B.: Advances in AI and Autonomous Vehicles: Cybernetic Self-Driving Cars Practical Advances in Artificial Intelligence (AI) and Machine Learning. LBE Press Publishing, 1st edn. (2017)
2017
Cited alongside, same era.
BBC: Honda to invest $2.8bn in GM’s self-driving car unit (2018), https://www.bbc.com/news/business-45728169
2018
Closest in time.
BBC: Jaguar self-drive car revealed in New York (2018), https://www.bbc.com/news/technology-43557798
2018
Closest in time.
Chen, Y., Wang, J., Li, J., Lu, C., Luo, Z., Xue, H., Wang, C.: Lidar-video driving dataset: Learning driving policies effectively. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2018)
2018
Closest in time.
2018
Closest in time.
Ma, L., Juefei-Xu, F., Sun, J., Chen, C., Su, T., Zhang, F., Xue, M., Li, B., Li, L., Liu, Y., et al.: Deepgauge: Multi-granularity testing criteria for deep learning systems. The 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE 2018) (2018)
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2017
Cited alongside, same era.
Huang, X., Kwiatkowska, M., Wang, S., Wu, M.: Safety verification of deep neural networks. In: International Conference on Computer Aided Verification. pp. 3–29 (2017)
2017
Cited alongside, same era.
Pei, K., Cao, Y., Yang, J., Jana, S.: Deepxplore: Automated whitebox testing of deep learning systems. In: Proceedings of the 26th Symposium on Operating Systems Principles. pp. 1–18 (2017)
2017
Cited alongside, same era.
2017
Cited alongside, same era.
BBC: AI image recognition fooled by single pixel change (2018), https://www.bbc.com/news/technology-41845878
2018
Cited alongside, same era.
BBC: Artificial intelligence ’did not miss a single urgent case’ (2018), https://www.bbc.com/news/health-44924948
2018
Cited alongside, same era.
BBC: Can we trust AI if we don’t know how it works? (2018), https://www.bbc.com/news/business-44466213
2018
Cited alongside, same era.
BBC: General Motors and Fiat Chrysler unveil self-driving deals (2018), https://www.bbc.com/news/business-44325629
2018
Cited alongside, same era.
2018
Closest in time.
Ma, L., Zhang, F., Sun, J., Xue, M., Li, B., Juefei-Xu, F., Xie, C., Li, L., Liu, Y., Zhao, J., et al.: Deepmutation: Mutation testing of deep learning systems. The 29th IEEE International Symposium on Software Reliability Engineering (ISSRE) (2018)
2018
Closest in time.
2018
Closest in time.
Ramanishka, V., Chen, Y.T., Misu, T., Saenko, K.: Toward driving scene understanding: A dataset for learning driver behavior and causal reasoning. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2018)
2018
Closest in time.
2018
Closest in time.
The New York Times: Alexa and Siri Can Hear This Hidden Command. You Can’t (2018), https://www.nytimes.com/2018/05/10/technology/alexa-siri-hidden-command-audio-attacks.html
2018
Closest in time.
The New York Times: Toyota, SoftBank Setting Up Mobility Services Joint Venture (2018), https://www.nytimes.com/aponline/2018/10/04/world/asia/ap-as-japan-toyota-softbank.html
2018
Closest in time.
Uber Accident: After Fatal Uber Crash, a Self-Driving Start-Up Moves Forward (2018), https://www.nytimes.com/2018/05/07/technology/uber-crash-autonomous-driveai.html
2018
Closest in time.