Search Results for author:
Found 5 papers, 3 papers with code
IEEE BigData 2023 Keystroke Verification Challenge (KVC)
Several neural architectures were proposed by the participants, leading to global Equal Error Rates (EERs) as low as 3. 33% and 3. 61% achieved by the best team respectively in the desktop and mobile scenario, outperforming the current state of the art biometric verification performance for KD.
Explanation-based Data Augmentation for Image Classification
This work proposes a framework that utilizes concept-based explanations to automatically augment the dataset with new images that can cover these under-represented regions to improve the model performance.
Towards Fully Interpretable Deep Neural Networks: Are We There Yet?
Despite the remarkable performance, Deep Neural Networks (DNNs) behave as black-boxes hindering user trust in Artificial Intelligence (AI) systems.
Comprehensible Convolutional Neural Networks via Guided Concept Learning
Learning concepts that are consistent with human perception is important for Deep Neural Networks to win end-user trust.
Real-Time Monitoring and Driver Feedback to Promote Fuel Efficient Driving
In this framework, a random-forest based classification model developed using historical data to identifies fuel-inefficient driving behaviors.
