3 papers
cs.CV2025
Effort-Optimized, Accuracy-Driven Labelling and Validation of Test Inputs for DL Systems: A Mixed-Integer Linear Programming Approach
Mohammad Hossein Amini, Mehrdad Sabetzadeh, Shiva Nejati
Software systems increasingly include AI components based on deep learning (DL). Reliable testing of such systems requires near-perfect test-input validity and label accuracy, with…
cs.SE2025
Test Input Validation for Vision-based DL Systems: An Active Learning Approach
Delaram Ghobari, Mohammad Hossein Amini, Dai Quoc Tran +3
Testing deep learning (DL) systems requires extensive and diverse, yet valid, test inputs. While synthetic test input generation methods, such as metamorphic testing, are widely us…
cs.SE2024
Bridging the Gap between Real-world and Synthetic Images for Testing Autonomous Driving Systems
Mohammad Hossein Amini, Shiva Nejati
Deep Neural Networks (DNNs) for Autonomous Driving Systems (ADS) are typically trained on real-world images and tested using synthetic simulator images. This approach results in tr…