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Publications

_{Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.}

| 2023 | 2022 | 2021 | 2020 |

2023

• Wu H, Yunas S, Rowlands S, Ruan W, Wahlstrom J. (2023) Adversarial Driving: Attacking End-to-End Autonomous Driving, IEEE Intelligent Vehicles Symposium, Proceedings, volume 2023-June, DOI:10.1109/IV55152.2023.10186386.
• Wu H, Yunas S, Rowlands S, Ruan W, Wahlstrom J. (2023) Adversarial Detection: Attacking Object Detection in Real Time, IEEE Intelligent Vehicles Symposium, Proceedings, volume 2023-June, DOI:10.1109/IV55152.2023.10186608.

2022

• Wu H, Rowlands S, Wahlstrom J. (2022) Distributed Black-box Attack against Image Classification Cloud Services. [PDF]
• Wu H, Rowlands S, Wahlstrom J. (2022) A Man-in-the-Middle Attack against Object Detection Systems. [PDF]
• Wu H, Yunas S, Rowlands S, Ruan W, Wahlstrom J. (2022) Adversarial Detection: Attacking Object Detection in Real Time, IEEE Intelligent Vehicle Symposium, 2023. [PDF]
• Liu H, Wang J, Geng Y, Li K, Wu H, Chen J, Chai X, Li S, Zheng D. (2022) Fine-Grained Assessment of COVID-19 Severity Based on Clinico-Radiological Data Using Machine Learning, Int J Environ Res Public Health, volume 19, no. 17, DOI:10.3390/ijerph191710665. [PDF]

2021

• Wu H, Yunas S, Rowlands S, Ruan W, Wahlstrom J. (2021) Adversarial Driving: Attacking End-to-End Autonomous Driving, IEEE Intelligent Vehicle Symposium, 2023. [PDF]

2020

• Wu H, Ruan W, Wang J, Zheng D, Liu B, Gen Y, Chai X, Chen J, Li K, Li S. (2020) Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task, IEEE Transactions on Artificial Intelligence, 2021. [PDF]

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