Ellis, A.-L. and Ferryman, J. (2014) Biologically-inspired robust motion segmentation using mutual information. Computer Vision and Image Understanding, 122. 47 - 64. ISSN 1077-3142 doi: 10.1016/j.cviu.2014.01.009
Ferryman, J. and Ellis, A.-L. (2014) Performance evaluation of crowd image analysis using the PETS2009 dataset. Pattern Recognition Letters, 44. pp. 3-15. ISSN 0167-8655 doi: 10.1016/j.patrec.2014.01.005
Panda, S. K., Jones, T. R.
ORCID: https://orcid.org/0000-0002-7669-1499, Shahzad, M.
ORCID: https://orcid.org/0009-0002-9394-343X, Lawrence, B.
ORCID: https://orcid.org/0000-0001-9262-7860 and Ellis, A.-L.
(2026)
Physics-guided multi-task learning for subgrid
scale turbulence parameterization: a comparative
study of physics integration strategies.
In: International Joint Conference on Neural Networks (IJCNN), SS03 Physics-Informed Neural Networks: Advancements and Applications, 21-26 June 2026, Maastricht, The Netherlands.
(In Press)
Ellis, A.-L. (2012) An eye for an eye: robust motion segmentation by applying the latest in human vision research. PhD thesis, University of Reading.