Usuario:Borja.ayerdi

De Grupo de Inteligencia Computacional (GIC)

Borja Ayerdi Vilches

Personal Data

  • E-mail: borja.ayerdi@ehu.es
  • Address:
Computational Intelligence Group
Computer Science Faculty - Lab. 307
University Of The Basque Country (UPV/EHU)
Paseo Manuel Lardizabal 1 - CP: 20018 Donostia/San Sebastián (GUIPUZCOA) - Spain
  • Tfno.: (+34) 943.01.80.47


Studies

PhD Student in the Computational Intelligence Group of the Computer Science and Artificial Intelligence Department - Universidad del País Vasco (UPV/EHU).


Research Areas

  • Medical Image segmentation and registration.
  • Machine Learning application to medical image processing.
  • Extreme Learning Machines.
  • Hyperspectral imaging.
  • Social Networks.
  • Big data.


Working experience

Project: EVARTRAC CIRUGÍA GUIADA POR IMAGEN: APLICACIÓN A LA REPARACIÓN ENDOVASCULAR DE ANEURISMAS DE AORTA.

Courses

  • Vitoria-Gasteiz 2009 - (Intensive Programme) Network Security and 4n6


Intership


Publications

2013

  • J. Maiora , G. García , B. Ayerdi , M. Graña , M. De Blas
"Active Learning enhanced with Expert Knowledge for Computed Tomography Image Segmentation"
InMed 2013, Greece, 17-19 July, 2013.


  • Borja Ayerdi, Josu Maiora, Manuel Graña
"Aplications of Hybrid Extreme Rotation Forests for Image Segmentation"
Journal of Hybrid Intelligent Systems


  • Borja Ayerdi, Josu Maiora, Manuel Graña
"Enhancing Active Learning Computed Tomography Image Segmentation with Domain Knowledge"
HAIS 2013, Salamanca, 11-13 September, 2013.


  • Borja Ayerdi, Alexandre Savio, Manuel Graña
"Meta-ensembles of classifiers for Alzheimer's disease detection using independent ROI features"
J.M. Ferrandez et al. (Eds.): IWINAC 2013, Part II, LNCS 7931, pp. 122--130. Springer, Heidelberg (2013)


  • Borja Ayerdi, Manuel Graña
"On Spatial Regularization for Semisupervised Hyperspectral Image Segmentation Using Hybrid Extreme Rotation Forest"
WHISPERS 2013, Gainesville, USA, 25-28 June, 2013.


  • Darya Chyzhyk, Borja Ayerdi, Josu Maiora
"Active Learning with Bootstrapped Dendritic Classifier applied to medical image segmentation"
Special Issue on KES 2012. Pattern Recognition Letters (Accepted, minor revision)
JCR 2011 - 1.034 (Q3 CSAI) / [5-Year Impact Factor: 1.724]


  • Josu Maiora, Borja Ayerdi, Manuel Graña
"Random Forest Active Learning for Computed Tomography Angiography Image Segmentation"
Neurocomputing (in press)
JCR 2011 - 1.580 (Q2 CSAI) / [5-Year Impact Factor: 1.595]


2012

  • Borja Ayerdi Vilches, Manuel Graña
"Hybrid Extreme Rotation Forest".
ELM 2012, Singapore, 11-13 December, 2012.


  • Borja Ayerdi, Josu Maiora, Manuel Graña
"Active learning of Hybrid Extreme Rotation Forests for CTA image segmentation".
Hybrid Intelligent Systems (HIS), 2012 12th International Conference on (pp. 543-548). IEEE.


2010

  • Ekaitz Zulueta Guerrero, Naiara Telleria Garay, Jose Manuel Lopez-Guede, Borja Ayerdi Vilches, Eider Egilegor Iragorri, David Lecumberri Castaños, Ana Belén de la Hoz Rastrollo and Carlos Pertusa Peña
"Prediction of Bladder Cancer Recurrences Using Artificial Neural Networks"
Lecture Notes in Computer Science, 2010, Volume 6076, Hybrid Artificial Intelligence Systems, Pages 492-499.


Conferences

  • HAIS 2013, Salamanca, 11-13 September, 2013. (???)
  • WHISPERS 2013, Gainesville, USA, 25-28 June, 2013.
  • IWINAC 2013, Mallorca, 10-14 June, 2013.
  • FIA 2013, Dublin, 8-10 May, 2013.
  • ELM 2012, Singapore, 11-13 December 2012.
  • HIS 2012, Pune (India), 04-07 December 2012.


Reviews

  • KES 2012
  • Pattern Recognition Letters
  • Neurocomputing
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS)


Organizer

  • Local organizing committee member of the 16th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems – (KES 2012) 10, 11 & 12 September 2012, San Sebastian, Spain.


Semana de la ciencia

  • XI Semana de la Ciencia 2011 (Diario Vasco)
  • XII Semana de la Ciencia 2012


Software

GIC Source Code

Hybrid Extreme Rotation Forest (HERF) basic code