Leveraging Classification Metrics for Quantitative System-Level Analysis with Temporal Logic Specifications

Author:

Badithela Apurva1,Wongpiromsarn Tichakorn2,Murray Richard M.1

Affiliation:

1. California Institute of Technology,Control and Dynamical Systems, Computing and Mathematical Sciences,Pasadena,CA,USA,91106

2. Iowa State University,Department of Computer Science,Ames,IA,USA,50011

Publisher

IEEE

Reference28 articles.

1. Safety verification and robustness analysis of neural networks via quadratic constraints and semidefinite programming;fazlyab;IEEE Transactions on Automatic Control,2020

2. NNV: The neural network verification tool for deep neural networks and learning-enabled cyber-physical systems;tran;International Conference on Computer Aided Verification,2020

3. Semantic Adversarial Deep Learning

4. Formal Specification for Deep Neural Networks

5. Compositional Falsification of Cyber-Physical Systems with Machine Learning Components

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2. Evaluation Metrics of Object Detection for Quantitative System-Level Analysis of Safety-Critical Autonomous Systems;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

3. Closed-Loop Analysis of Vision-Based Autonomous Systems: A Case Study;Computer Aided Verification;2023

4. Design and Evaluation of Object Classifiers for Probabilistic Decision-Making in Autonomous Systems;2022 International Conference on Robotics and Automation (ICRA);2022-05-23

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