Ethan Goan
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I am a research fellow at QUT in the school of Electrical Engineering and Robotics, where I also completed my PhD in 2024 and my undergraduate in Electrical Engineering. My research focuses on uncertainty quantification in computer vision, machine learning and biomechanics. I have interests in statistics, embedded systems, Emacs, and much more which I may/may not occasionally write about.
You can contact me at: ej <dot> goan <at> qut <dot> edu <dot> au
Publications
W. Xiao, E. Goan, R. Santa Cruz, D. Ahmedt-Aristizabal, O. Salvado, C. Fookes, and L. Lebrat. In depth we trust: Reliable monocular depth supervision for gaussian splatting. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2026. paper to appear soon
A. Pemasiri, E. Goan, G. Lichtwark, R. Schuster, L. Kelly, and C. Fookes. Biomechanically accurate gait analysis: A 3d human reconstruction framework for markerless estimation of gait parameters. In IEEE International Symposium on Biomedical Imaging (ISBI), 2026. [paper]
A. Pemasiri, Z. Huang, F. Williams, E. Goan, S. Denman, T. Martin, and C. Fookes. Automatic radar signal detection and fft estimation using deep learning. In 17th International Conference on Signal Processing and Communication Systems. IEEE, 2024. [paper]
E. Goan and C. Fookes. Uncertainty in real-time semantic segmentation on embedded systems. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops [paper with errata] [code] [errata]
E. Goan, D. Perrin, K. Mengersen, and C. Fookes. Piecewise deterministic markov processes for bayesian neural networks. In Uncertainty in Artificial Intelligence, 2023. [paper with errata] [code] [errata]
O. Tursun, S. Denman, S. Sridharan, E. Goan, and C. Fookes. An efficient framework for zero-shot sketch-based image retrieval. Pattern Recognition, 126:108528, 2022. [paper]
S. K. Sieberts, J. Schaff, M. Duda, B. Á. Pataki, M. Sun, P. Snyder, J.-F. Daneault, F. Parisi, G. Costante, U. Rubin, and others. Crowdsourcing digital health measures to predict parkinson’s disease severity: the parkinson’s disease digital biomarker dream challenge. NPJ digital medicine, 4(1):53, 2021. [paper]
E. Goan and C. Fookes. Bayesian neural networks: An introduction and survey. Case Studies in Applied Bayesian Data Science 2020. [paper]
T. Schaffter, D. S. Buist, C. I. Lee, Y. Nikulin, D. Ribli, Y. Guan, W. Lotter, Z. Jie, H. Du, S. Wang, and others. Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms. JAMA network open, 2020. [paper]
P. Moghadam, D. Ward, E. Goan, S. Jayawardena, P. Sikka, and E. Hernandez. Plant disease detection using hyperspectral imaging. In 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), pages 1–8. IEEE, 2017. [paper]
R. Arablouei, E. Goan, S. Gensemer, and B. Kusy. Fast and robust pushbroom hyperspectral imaging via dmd-based scanning. In Novel Optical Systems Design and Optimization XIX, SPIE, 2016. [paper]
Errata for my articles: [errata]