Smooth grad-cam++: An enhanced inference level visualization technique for deep convolutional neural network models D Omeiza, S Speakman, C Cintas, K Weldermariam arXiv preprint arXiv:1908.01224, 2019 | 289 | 2019 |
Explanations in autonomous driving: A survey D Omeiza, H Webb, M Jirotka, L Kunze IEEE Transactions on Intelligent Transportation Systems, 2021 | 283 | 2021 |
Deep convolutional neural network for plant seedlings classification DK Nkemelu, D Omeiza, N Lubalo 2018 NeurIPS Black in AI Workshop, 2018 | 60 | 2018 |
A Fait Accompli? An Empirical Study into the Absence of Consent to Third-Party Tracking in Android~ Apps K Kollnig, R Binns, P Dewitte, M Van Kleek, G Wang, D Omeiza, H Webb, ... SOUPS Conference, 2021 | 50 | 2021 |
Towards accountability: providing intelligible explanations in autonomous driving DA Omeiza, H Webb, M Jirotka, L Kunze In the Proceedings of the 2021 IEEE Intelligent Vehicles Symposium, 2021 | 43 | 2021 |
Smooth grad-cam++: An enhanced inference level visualization technique for deep convolutional neural network models. arXiv 2019 D Omeiza, S Speakman, C Cintas, K Weldermariam arXiv preprint arXiv:1908.01224, 1908 | 35 | 1908 |
Rag-driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi-modal large language model J Yuan, S Sun, D Omeiza, B Zhao, P Newman, L Kunze, M Gadd Proceedings of Robotics: Science and Systems, 2024 | 34 | 2024 |
Assessing and explaining collision risk in dynamic environments for autonomous driving safety R Nahata, D Omeiza, R Howard, L Kunze 24th IEEE International Conference on Intelligent Transportation Systems, 2021 | 33 | 2021 |
Why not explain? effects of explanations on human perceptions of autonomous driving D Omeiza, K Kollnig, H Web, M Jirotka, L Kunze 2021 IEEE international conference on advanced robotics and its social …, 2021 | 27 | 2021 |
Context-based image explanations for deep neural networks S Anjomshoae, D Omeiza, L Jiang Image and Vision Computing 116, 104310, 2021 | 20 | 2021 |
From Spoken Thoughts to Automated Driving Commentary: Predicting and Explaining Intelligent Vehicles' Actions D Omeiza, S Anjomshoae, H Webb, M Jirotka, L Kunze In Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022 | 15 | 2022 |
Realizing the Potential of AI in Africa: It All Turns on Trust CD Alupo, D Omeiza, D Vernon Towards Trustworthy Artificial Intelligent Systems, pp. 179-192, 2021 | 14 | 2021 |
Explainable Action Prediction through Self-Supervision on Scene Graphs P Kochakarn, D De Martini, D Omeiza, L Kunze International Conference on Robotics Automation (ICRA), 2023 | 10 | 2023 |
Fairness and transparency in human-robot interaction H Claure, ML Chang, S Kim, D Omeiza, M Brandao, MK Lee, M Jung 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2022 | 8 | 2022 |
Textual Explanations for Automated Commentary Driving MA Kühn, D Omeiza, L Kunze IEEE Intelligent Vehicles Symposium (IV) 2023, 2023 | 7 | 2023 |
Towards Explainable and Trustworthy Autonomous Physical Systems D Omeiza, S Anjomshoae, K Kollnig, OM Camburu, K Främling, L Kunze Proceedings of the CHI Conference on Human Factors in Computing Systems, 1-3, 2021 | 7 | 2021 |
Web security investigation through penetration tests: A case study of an educational institution portal D Omeiza, J Owusu-Tweneboah arXiv preprint arXiv:1811.01388, 2018 | 5 | 2018 |
A Step Towards Exposing Bias in Trained Deep Convolutional Neural Network Models D Omeiza 2019 NeurIPS Workshop on Machine Learning for Developing World, 2019 | 3 | 2019 |
Efficient Machine Learning for Large-Scale Urban Land-Use Forecasting in Sub-Saharan Africa D Omeiza, D Vernon arXiv preprint arXiv:1908.00340, 2019 | 3 | 2019 |
CC-SGG: Corner Case Scenario Generation using Learned Scene Graphs G Drayson, E Panagiotaki, D Omeiza, L Kunze arXiv preprint arXiv:2309.09844, 2023 | 2 | 2023 |