Selected Publications (2017-2011)

  1. S.H. Lee, C.S. Chan, S.J. Mayo, P.Remagnino, How Deep learning extracts and learns leaf features for plant classification, Elsevier Pattern Recognition 71(Nov):1-13, 2017.
  2. P. Remagnino, S.J. Mayo, P. Wilkin, J. Cope, D. Kirkup, Computational Botany: Methods for Automated Species Identification, Springer, 2017.
  3. F. Gu, M. Sridhar, A. Cohn, D. Hogg, D.N. Monekosso, P. Remagnino, Weakly supervised analysis with spatio-temporal localization, Elsevier Neurocomputing, 216(Dec):778-789, 2016.
  4. F. Gu, D.N. Monekosso, P. Remagnino, Marginalised Stacked Denoising Autoencoders for Robust Representation of Real-Time Multi-View Action Recognition Sensors 15(7):17209-17231, 2015.
  5. M.K. Lim, C.S. Chan, D.N. Monekosso, P. Remagnino, Refined particle swarm intelligence
    method for abrupt motion tracking, Information Sciences 283, 267-287, 2014.
  6. M.K. Lim, C.S. Chan, D.N. Monekosso, P. Remagnino, Detection of salient regions in crowded scenes, IET Electronics Letters 50(5):363-365, 2014.
  7. R. Grech, D.N. Monekosso, P. Remagnino, Robot Teams: Sharing Visual memories, in Proceedings of the International Symposium on Distributed Autonomous Robotic Systems, 104:369-381, 2014.
  8. P. Climent-Pérez, A. Mauduit, D.N. Monekosso, P. Remagnino, Detecting events in crowded scenes using tracklet plots, in Proceedings of the International Conference on Computer Vision Theory and Applications, 2:174-181, 2014.
  9. M. Thida, H-L. Eng, D.N. Monekosso, P. Remagnino, A particle swarm optimisation algorithm with interactive swarms for tracking multiple targets, Applied Soft Computing 13(6):3106-3117, 2013.
  10. M. Thida, Y.L. Yong, P. Climent-Pérez, H-L. Eng, P. Remagnino, A literature review on video analytics of crowded scenes, Intelligent Multimedia Surveillance, pp. 17-36, 2013.
  11. M. Thida, H-L. Eng, P. Remagnino, Laplacian Eigenmap with temporal constraints for local abnormality detection in crowded scenes, IEEE Transactions on Cybernetics, 43(6):2147-2156, 2013.