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Deep Neural Networks (DNN) will emerge as a cornerstone in automotive software engineering.
610.12-1990 IEEE standard glossary of software engineering terminology
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Implementing fail-silent nodes for distributed systems
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Certifying Adaptive Flight Control Software
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Verification of a trained neural network accuracy
R. R. Zakrzewski · 2001
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Verification and validation of neural networks for safety-critical applications
J. Hull, D. Ward, and R. R. Zakrzewski · 2002
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Verification and validation of neural networks for aerospace systems
D. Mackall, S. Nelson, and J. Schumman · 2002
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Toward V&V of Neural Network Based Controllers
Johann Schumann and Stacy Nelson · 2002
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Verification of performance of a neural network estimator
R. R. Zakrzewski · 2002
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Verification and validation of neural networks: a sampling of research in progress
Brian J. Taylor, Marjorie A. Darrah, and Christina D. Moats · 2003
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Lyapunov Analysis of Neural Network Stability in an Adaptive Flight Control System
Sampath Yerramalla, Edgar Fuller, Martin Mladenovski, and Bojan Cukic · 2003
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Statistical and adaptive approach for verification of a neural-based flight control system
R. L. Broderick · 2004
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Verification and Validation Methodology of Real-time Adaptive Neural Networks for Aerospace Applications
P. Gupta, Ph D, K. A. Loparo, Ph D, D. Mackall, J. Schumann, Ph D, and F. R. Soares · 2004
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A tool for verification and validation of neural network based adaptive controllers for high assurance systems
P. Gupta and J. Schumann · 2004
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Verification, Validation, and Certification Challenges for Adaptive Flight-Critical Control System Software
Stephen Jacklin, Johann Schumann, Pramod Gupta, M Lowry, John Bosworth, Eddie Zavala, Kelly Hayhurst, Celeste Belcastro, and Christine Belcastro · 2004
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Towards the verification and validation of online learning systems: general framework and applications
A. Mili, GuangJie Jiang, B. Cukic, Yan Liu, and R. B. Ayed · 2004
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Randomized approach to verification of neural networks
R. R. Zakrzewski · 2004
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Challenges in verification and validation of autonomous systems for space exploration
G. Brat and A. Jonsson · 2005
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Adaptive verification for an on-line learning neural-based flight control system
R. L. Broderick · 2005
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Performance Monitoring and Assessment of Neuro-Adaptive Controllers for Aerospace Applications Using a Bayesian Approach
Pramod Gupta, Kurt Guenther, John Hodgkinson, Stephen Jacklin, Michael Richard, Johann Schumann, and Fola Soares · 2005
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Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications
Stephen Jacklin, Johann Schumann, Pramod Gupta, Michael Richard, Kurt Guenther, and Fola Soares · 2005
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Toward Verification and Validation of Adaptive Aircraft Controllers
J. Schumann, P. Gupta, and S. Jacklin · 2005
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An Approach to V&V of Embedded Adaptive Systems
Sampath Yerramalla, Yan Liu, Edgar Fuller, Bojan Cukic, and Srikanth Gururajan · 2005
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Case Study: Test Results of a Tool and Method for In-Flight, Adaptive Control System Verification on a NASA F-15 Flight Research Aircraft
Stephen A. Jacklin, Johann Schumann, John T. Bosworth, Peggy S. Williams-Hayes, and Richard S. Larson · 2006
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A Flight Test Demonstration of On-line Neural Network Applications in Advanced Aircraft Flight Control System
F. Soares and J. Burken · 2006
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Neural Network Applications in Advanced Aircraft Flight Control System, a Hybrid System, a Flight Test Demonstration
Fola Soares, John Burken, and Tshilidzi Marwala · 2006
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Methods and Procedures for the Verification and Validation of Artificial Neural Networks
Brian J. Taylor · 2006
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Flight Test Results from the NF-15b Intelligent Flight Control System Project with Adaptation to a Simulated Stabilitor Failure
J. Bosworth and P. Williams-Hayes · 2007
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Real Time Road Signs Recognition
A. Broggi, P. Cerri, P. Medici, P. P. Porta, and G. Ghisio · 2007
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Developing artificial neural networks for safety critical systems
Zeshan Kurd, Tim Kelly, and Jim Austin · 2007
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Validating neural network-based online adaptive systems: a case study
Yan Liu, Bojan Cukic, and Srikanth Gururajan · 2007
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Neural Net Adaptive Flight Control Stability
Nhan T. Nguyen and Stephen A. Jacklin · 2007
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Guidance for the Verification and Validation of Neural Networks
Laura Pullum, Brian Taylor, and Majorie Darrah · 2007
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Tools and Methods for the Verification and Validation of Adaptive Aircraft Control Systems
J. Schumann and Y. Liu · 2007
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Closing the Certification Gaps in Adaptive Flight Control Software
Stephen Jacklin · 2008
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Principles of engineering safety: Risk and uncertainty reduction
Niklas Moller and Sven Ove Hansson · 2008
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IEC 61508 ed 1.0, Electrical/electronic/programmable electronic safety-related systems
{International Electrotechnical Commission} · 2010
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A Scenario-Based Method for Safety Certification of Artificial Intelligent Software
G. Li, M. Lu, and B. Liu · 2010
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Stability, Convergence, and Verification and Validation Challenges of Neural Net Adaptive Flight Control
Nhan T. Nguyen and Stephen A. Jacklin · 2010
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An Abstraction-Refinement Approach to Verification of Artificial Neural Networks
Luca Pulina and Armando Tacchella · 2010
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Application of Neural Networks in High Assurance Systems: A Survey
Johann Schumann, Pramod Gupta, and Yan Liu · 2010
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Recommended Steps for Thematic Synthesis in Software Engineering
D. S. Cruzes and T. Dyba · 2011
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Domain Adaptation for Large-scale Sentiment Classification: A Deep Learning Approach
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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Towards Verification of Artificial Neural Networks
Karsten Scheibler, Leonore Winterer, Ralf Wimmer, and Bernd Becker · 2015
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Formal Methods for Semi-autonomous Driving
Sanjit A. Seshia, Dorsa Sadigh, and S. Shankar Sastry · 2015
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Going Deeper With Convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Controller Verification in Adaptive Learning Systems Towards Trusted Autonomy
Xiaodong Zhang, Matthew Clark, Kudip Rattan, and Jonathan Muse · 2015
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Safety Engineering for Autonomous Vehicles
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Xavier Glorot, Antoine Bordes, and Yoshua Bengio · 2011
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Safe Automotive Software
Karl Heckemann, Manuel Gesell, Thomas Pfister, Karsten Berns, Klaus Schneider, and Mario Trapp · 2011
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ISO 26262 Road vehicles - Functional safety
{International Organization for Standardization} · 2011
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A method for evaluating rigor and industrial relevance of technology evaluations
Martin Ivarsson and Tony Gorschek · 2011
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NeVer: a tool for artificial neural networks verification
Luca Pulina and Armando Tacchella · 2011
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Using neural networks to assess human-automation interaction
K. B. Sullivan, K. M. Feigh, F. T. Durso, U. Fischer, V. L. Pop, K. Mosier, J. Blosch, and D. Morrow · 2011
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Design of a Robust Plausibility Check for an Adaptive Vehicle Observer in an Electric Vehicle
Matthias Korte, Frédéric Holzmann, Gerd Kaiser, Volker Scheuch, and Hubert Roth · 2012
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R. Adler, P. Feth, and D. Schneider · 2016
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Concrete Problems in AI Safety
Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mane · 2016
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Testing advanced driver assistance systems using multi-objective search and neural networks
Raja Ben Abdessalem, Shiva Nejati, Lionel C Briand, and Thomas Stifter · 2016
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VisualBackProp: efficient visualization of CNNs
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End to End Learning for Self-Driving Cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, and Karol Zieba · 2016
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NIPS 2016 Tutorial: Generative Adversarial Networks
Ian Goodfellow · 2016
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DeepLanes: End-To-End Lane Position Estimation Using Deep Neural Networks
A. Gurghian, T. Koduri, S. Bailur, K. Carey, and V. Murali · 2016
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Testing of Autonomous Systems - Challenges and Current State-of-the-Art
P. Helle, W. Schamai, and C. Strobel · 2016
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Safety Verification of Deep Neural Networks
Xiaowei Huang, Marta Kwiatkowska, Sen Wang, and Min Wu · 2016
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Intelligence Testing for Autonomous Vehicles: A New Approach
L. Li, W. L. Huang, Y. Liu, N. N. Zheng, and F. Y. Wang · 2016
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Nan Li, Dave Oyler, Mengxuan Zhang, Yildiray Yildiz, Ilya Kolmanovsky, and Anouck Girard · 2016
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D. Maji, A. Santara, P. Mitra, and D. Sheet · 2016
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Detecting Unexpected Obstacles for Self-Driving Cars: Fusing Deep Learning and Geometric Modeling
Sebastian Ramos, Stefan Gehrig, Peter Pinggera, Uwe Franke, and Carsten Rother · 2016
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Research Priorities for Robust and Beneficial Artificial Intelligence
S. Russell, D. Dewey, and M. Tegmark · 2016
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End-to-End Deep Reinforcement Learning for Lane Keeping Assist
Ahmad Sallab, Mohammed Abdou, Etienne Perot, and Senthil Yogamani · 2016
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Towards Verified Artificial Intelligence
Sanjit A. Seshia, Dorsa Sadigh, and S. Shankar Sastry · 2016
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Efficient Statistical Validation of Machine Learning Systems for Autonomous Driving
Weijing Shi, Mohamed Baker Alawieh, Xin Li, Huafeng Yu, Nikos Arechiga, and Nobuyuki Tomatsu · 2016
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RenderGAN: Generating Realistic Labeled Data
Leon Sixt, Benjamin Wild, and Tim Landgraf · 2016
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Alignment for advanced machine learning systems
J. Taylor, E. Yudkowsky, P. LaVictoire, and A. Critch · 2016
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Engineering safety in machine learning
K. Varshney · 2016
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On the Validation of a UAV Collision Avoidance System Developed by Model-Based Optimization: Challenges and a Tentative Partial Solution
X. Zou, R. Alexander, and J. McDermid · 2016
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Accelerator Design for Deep Learning Training: Extended Abstract: Invited
Ankur Agrawal, Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Jinwook Oh, Sunil Shukla, Viji Srinivasan, Swagath Venkataramani, and Wei Zhang · 2017
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Traceability and Deep Learning - Safety-critical Systems with Traces Ending in Deep Neural Networks
M. Borg, C. Englund, and B. Duran · 2017
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Deep Learning in Automotive Software
F. Falcini, G. Lami, and A. Costanza · 2017
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Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz, Clark Barrett, David Dill, Kyle Julian, and Mykel Kochenderfer · 2017
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Software-related Challenges of Testing Automated Vehicles
Alessia Knauss, Jan Schroeder, Christian Berger, and Henrik Eriksson · 2017
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On The Robustness of a Neural Network
E. Mhamdi, Rachid Guerraoui, and Sebastien Rouault · 2017
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An Analysis of ISO 26262: Using Machine Learning Safely in Automotive Software
Rick Salay, Rodrigo Queiroz, and Krzysztof Czarnecki · 2017
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Overview of Environment Perception for Intelligent Vehicles
H. Zhu, K. Yuen, L. Mihaylova, and H. Leung · 2017
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Automotive safety and machine learning: Initial results from a study on how to adapt the iso 26262 safety standard
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