Publications

 

Journal papers
  1. B. Gecer, G. Azzopardi, and N. Petkov, “Color-blob-based COSFIRE filters for Object Recognition” Image and Vision Computing, vol. 57, pp. 165-174, 2017.
    [Impact Factor: 1.77] [abstract] [pdf] [bib]
  2. L. Fernandez Robles, G. Azzopardi, E. Alegre, and N. Petkov, “Machine-vision-based identification of broken inserts in edge profile milling heads” Robotics and Computer-Integrated Manufacturing, vol. 44, pp. 276-283, 2017.
    [Impact Factor: 2.077] [abstract] [pdf] [bib]
  3. N. Strisciuglio, G. Azzopardi, M. Vento, and N. Petkov, “Supervised vessel delineation in retinal fundus images with the automatic selection of B-COSFIRE filters” Machine Vision and Applications, doi: 10.1007/s00138-016-0781-7, 2016.
    [Impact Factor: 1.351] [abstract] [pdf] [bib]
  4. J. Guo, C. Shi, G. Azzopardi, N. Petkov, “Inhibition-augmented trainable COSFIRE filters for keypoint detection and object recognition” Machine Vision and Applications, doi: 10.1007/s00138-016-0777-3, 2016.
    [Impact Factor: 1.351] [abstract] [pdf] [bib]
  5. G. Azzopardi, N. Strisciuglio, M. Vento, and N. Petkov, “Trainable COSFIRE filters for vessel delineation with application to retinal images” Medical Image Analysis, vol. 19 (1), pp. 46-57, 2015.
    [Impact Factor: 3.68] [abstract] [pdf] [bib] Top 1%
  6. G. Azzopardi, and N. Petkov, “Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models” Frontiers in Computational Neuroscience, vol. 8(80), 2014.
    [Impact Factor: 2.5] [abstract] [pdf] [bib]
  7. G. Azzopardi, A. Rodriguez Sanchez, J. Piater and N. Petkov, “A push-pull CORF model of a simple cell with antiphase inhibition improves SNR and contour detection”, PLOS ONE, vol. 9 (7): e98424. doi:10.1371/journal.pone.0098424, 2014.
    [Impact Factor: 3.73] [abstract] [pdf] [bib]
  8. G. Azzopardi and N. Petkov, “Automatic detection of vascular bifurcations in segmented retinal images using trainable COSFIRE filters”, Pattern Recognition Letters, vol. 34 (8), pp. 922-933, 2013.
    [Impact Factor: 1.06] [abstract] [pdf] [bib] [matlab]
  9. G. Azzopardi and N. Petkov, “Trainable COSFIRE filters for keypoint detection and pattern recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35 (2), pp. 490-503, 2013.
    [Impact Factor: 5.7] [abstract] [pdf] [bib] [matlab]
  10. G. Azzopardi and N. Petkov, “A CORF computational model of a simple cell outperforms the Gabor function model”, Biological Cybernetics, vol. 106 (3), pp. 177-189, 2012
    [Impact Factor: 1.93] [abstract] [pdf] [bib] [matlab]
Chapters in conference proceedings
  1. G. Azzopardi, A. Greco, M. Vento: “Gender recognition from face images with trainable COSFIRE filters”, 13th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Colorado Springs, CO, USA, 2016, pp. 235-241.
    [abstract] [pdf] [bib]
  2. G. Azzopardi, A. Greco, M. Vento: “Gender Recognition from Face Images Using a Fusion of SVM Classifiers”, Proceedings of ICIAR 2016 (Póvoa de Varzim, Portugal), Volume 9730 of the series Lecture Notes in Computer Science, pp 533-538
    [abstract] [pdf] [bib]
  3. C. Shi, J. M. Meijer, J. Guo, G. Azzopardi, M. F. Jonkman, N. Petkov: “Automatic Classification of Serrated Patterns in Direct Immunofluorescence Images”, Autonomous Systems 2015 – Proceedings of the 8th GI Conference, Fortschritt-Berichte VDI, Reihe 10 Nr. 842, (Dusseldorf: VDI Verlag, 2015), pp. 61-69, 2015.
    [abstract] [pdf] [bib]
  4. N. Strisciuglio, M. Vento, G. Azzopardi, N. Petkov: Unsupervised delineation of the vessel tree in retinal fundus images. Computational Vision and Medical Image Processing VIPIMAGE 2015, J. Tavares and R.M. Natal Jorge (Eds.), (CRC Press/Balkema, Taylor and Francis Group; Leiden, NL, 2016) pp 149-155.
    [abstract] [pdf] [bib] Best Paper Award
  5. Henri Bouma, Pieter T. Eendebak, Klamer Schutte, George Azzopardi, Gertjan J. Burghouts, “Incremental concept learning with few training examples and hierarchical classification”, Proc. SPIE, vol. 9652, 2015.
    [abstract] [pdf] [bib]
  6. N. Strisciuglio, G. Azzopardi, M. Vento, N. Petkov, “Multiscale Blood Vessel Delineation Using B-COSFIRE Filters”, Proceedings Part II of CAIP2015, LNCS 9257, pp. 300-312, 2015
    [abstract] [pdf] [bib]
  7. J. Guo, C. Shi, G. Azzopardi, N. Petkov, “Recognition of Architectural and Electrical Symbols by COSFIRE Filters with Inhibition”, Proceedings Part II of CAIP2015, LNCS 9257, pp. 348-358, 2015
    [abstract] [pdf] [bib]
  8. A. C. Neocleous, G. Azzopardi, C. Schizas, N. Petkov,
 “Filter-Based Approach for Ornamentation Detection and Recognition in Singing Folk Music”, Proceedings Part I of CAIP2015, LNCS 9256, pp. 558-569, 2015
    [abstract] [pdf] [bib]
  9. L. Fernández-Robles, G. Azzopardi, E. Alegre, N. Petkov, “Cutting Edge Localisation in an Edge Profile Milling Head”, Proceedings Part II of CAIP2015, LNCS 9257, pp. 336-347, 2015
    [abstract] [pdf] [bib]
  10. C. Shi, J. Guo, G. Azzopardi, J. M. Meijer, M. F. Jonkman, N. Petkov, “Automatic Differentiation of u- and n-serrated Patterns in Direct Immunofluorescence Images”, Proceedings Part I of CAIP2015, LNCS 9256, pp. 513-521, 2015.
    [abstract] [pdf] [bib]
  11. K. Schutte, H. Bouma, J. Schavemaker, L. Daniele, M. Sappelli, G. Koot, P. Eendebak, G. Azzopardi, M. Spitters, M. de Boer, M. Kruithof and Paul Brandt, “Interactive detection of incrementally learned concepts in images”, IEEE/ACM International Workshop on Content-Based Multimedia Indexing (CBMI), 2015.
    [abstract] [pdf] [bib]
  12. G. Azzopardi, N. Petkov, “COSFIRE: A brain-inspired approach to visual pattern recognition”, BrainComp, Cetraro, Italy, Lecture Notes in Computer Science, vol. 8603, 2014
    [abstract] [pdf] [bib]
  13. H. de Vries, G. Azzopardi, A. Knobbe, A. Koelewijn, “Parametric nonlinear regression models for dike monitoring systems”, IDA, Leuven, Belgium, Advances in Intelligent Data Analysis, LNCS, vol. 8819, pp. 345-355, 2014
    [abstract] [pdf] [bib]
  14. H. Bouma, G. Azzopardi, et al., “TNO at TRECVID 2013: Multimedia Event Detection and Instance Search”, Proceedings of TRECVID, Maryland, USA, 2013.
    [abstract] [pdf] [bib]
  15. G. Azzopardi and N. Petkov, “A shape descriptor based on trainable COSFIRE filters for the recognition of handwritten digits”, Computer Analysis of Images and Patterns (CAIP, York, United Kingdom) Lecture Notes in Computer Science vol. 8048, pp. 9-16, 2013.
    [abstract] [pdf] [bib] [presentation]
  16. G. Azzopardi and N. Petkov, “Contour Detection by CORF Operator”, International Conference on Artifical Neural Networks (ICANN, Lausanne, Switzerland) Lecture Notes in Computer Science, vol. 7552, pp. 395-402, 2012.
    [abstract] [pdf] [bib][presentation]
  17. G. Azzopardi and N. Petkov, “Detection of retinal vascular bifurcations by rotation-, scale- and reflection-invariant COSFIRE filters”, Computer Based Medical System (CBMS, Università Campus Bio-Medico di Roma, Italy) IEEE, pp. 1-4, 2012.
    [abstract] [pdf] [bib]
  18. G. Azzopardi and N. Petkov, “Detection of retinal vascular bifurcations by rotation- and scale-invariant COSFIRE filters”, Computer Analysis of Images and Patterns (ICIAR, Aveiro, Portugal) Lecture Notes in Computer Science vol. 7325, pp. 363-371, 2012.
    [abstract] [pdf] [bib]
  19. G. Azzopardi and N. Petkov, “Detection of Retinal Vascular Bifurcations by Trainable V4-Like Filters”, Computer Analysis of Images and Patterns (CAIP, Seville, Spain), Lecture Notes in Computer Science vol. 6854, 2011, pp. 451-459, 2011.
    [abstract] [pdf] [bib] [poster] [presentation] [ground truth data] [web application]
  20. G. Azzopardi and F. Smeraldi, “Variance Ranklets: orientation-selective rank features for contrast modulations”, in BMVC Queen Mary, London UK, 2009.
    [abstract] [pdf] [bib] [poster] [Wikipedia] [matlab script]
  21. G. Azzopardi and K. P. Camilleri, “Offline Handwritten Signature Verification using Radial Basis Function Neural Networks”, in WICT, Malta, 2008.
    [abstract] [pdf] [bib] [poster] [presentation]

 

Conferences: poster presentations
  1. H. Bouma, P. T. Eendebak, K. Schutte, G. Azzopardi, G. J. Burghouts, “Incremental concept learning with few training examples and hierarchical classification”, SPIE Conference: Optics and photonics for counter terrorism, crime fighting and defence, Toulouse, Sep 2015.
  2. G. Azzopardi and N. Petkov, “A computational model of push-pull inhibition of simple cells with application to contour detection”, ECVP, Belgrade, Serbia, 2014.
    [abstract] [poster]
  3. W. Wijbrandi, E. Lazovik, G. Azzopardi, F. Pierie, “A Decision Support System for Planning of Flexible Biogas Chains”, EU BC&E, Hamburg, Germany, June, 2014.
    [abstract] [poster]
  4. G. Azzopardi, N. Strisciuglio, M. Vento and N. Petkov, “Vessel delineation in retinal images using COSFIRE filters”, NCCV, Ermelo, Netherlands, April, 2014.
    [abstract] [pdf] [presentation]
  5. G. Azzopardi and N. Petkov, “Trainable Filtering Approach to Object Recognition and Localization”, AISTATS, Rejkjavik, Iceland, April, 2014.
    [poster]
  6. G. Azzopardi, “GOOSE: Search on internet of connected sensors”, International workshop on brain-inspired computing, Cetraro, Italy, July 2013.
    [abstract] [presentation]
  7. G. Azzopardi and N. Petkov, “COSFIRE: A trainable features approach to pattern recognition”, Benelearn, Nijmegen, Netherlands, June 2013
    [abstract] [presentation]
  8. G. Azzopardi and N. Petkov, “CORF: A computational model of a simple cell with application to contour detection”, ECVP, Alghero, Sardinia, Italy, Sep 2012.
    [abstract] [poster]
  9. G. Azzopardi and N. Petkov, “A CORF computational model of a simple cell with application to contour detection”, AVA/BMVA Meeting on Biological and Computer Vision, Microsoft Research Center, Cambridge, UK, May 2012
    [abstract] [poster]
  10. G. Azzopardi and N. Petkov, “V4-like filters applied to the detection of retinal vascular bifurcations”, AVA/BMVA Meeting on Biological and Computer Vision, School of Psychology, Cardiff University, Wales, May 2011
    [abstract] [poster]