Mots-clés

Nombre de documents

26

Pablo Mesejo


My name is Pablo Mesejo Santiago and I currently hold a Marie Curie Experienced Researcher position at the University of Granada (Spain), one of the top institutions in computer science and engineering.

My principal research areas of interest are computer vision, machine learning and computational intelligence methods applied to image analysis problems (mainly in the biomedical domain). Typical tools I use in my research are stochastic optimization algorithms, deep and shallow neural networks, and ensemble classifiers. During my career I have tackled numerous challenging problems, e.g. the automatic segmentation of anatomical structures in biomedical images (PhD at University of Parma, performed as a Marie Curie Early Stage Researcher, 2010-13), the classification of gastrointestinal lesions from endoscopic videos (postdoc at University of Auvergne Clermont-Ferrand I, 2013-14), the estimation of biophysical parameters from fMRI signals (postdoc at Inria, 2014-16), and the integration of deep learning into probabilistic generative models for visual and audio recognition in human-robot interaction (starting researcher position at Inria, 2016-18).

More information about me and my publications can be found in the following links: personal webpage, Google Scholar, ORCID, Linkedin, DBLP, ResearchGate and ResearcherID.


Article dans une revue11 documents

  • Stéphane Lathuilière, Benoît Massé, Pablo Mesejo, Radu Horaud. Neural Network Based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction. Pattern Recognition Letters, Elsevier, 2018, 〈10.1016/j.patrec.2018.05.023〉. 〈hal-01643775v2〉
  • Pablo Mesejo, Daniel Pizarro, Armand Abergel, Olivier Rouquette, Sylvain Beorchia, et al.. Computer-Aided Classification of Gastrointestinal Lesions in Regular Colonoscopy. IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2016, 35 (9), pp.2051 - 2063. 〈10.1109/TMI.2016.2547947〉. 〈hal-01291797v2〉
  • Pablo Mesejo, Sandrine Saillet, Olivier David, Christian Bénar, Jan M. Warnking, et al.. A differential evolution-based approach for fitting a nonlinear biophysical model to fMRI BOLD data. IEEE Journal of Selected Topics in Signal Processing, IEEE, 2016, 10 (2), pp.416-427. 〈10.1109/JSTSP.2015.2502553〉. 〈hal-01221115v2〉
  • Pablo Mesejo, Oscar Ibáñez, Oscar Cordón, Stefano Cagnoni. A Survey on Image Segmentation using Metaheuristic-based Deformable Models: State of the Art and Critical Analysis. Applied Soft Computing, Elsevier, 2016, 44, pp.1-29. 〈10.1016/j.asoc.2016.03.004〉. 〈hal-01282678〉
  • Pablo Mesejo, Óscar Ibáñez, Enrique Fernández-Blanco, Francisco Cedrón, Alejandro Pazos, et al.. Artificial Neuron–Glia Networks Learning Approach Based on Cooperative Coevolution. International Journal of Neural Systems, World Scientific Publishing, 2015, 25 (4), 〈10.1142/S0129065715500124〉. 〈hal-01221226〉
  • Pablo Mesejo, Andrea Valsecchi, Linda Marrakchi-Kacem, Stefano Cagnoni, Sergio Damas. Biomedical image segmentation using geometric deformable models and metaheuristics. Computerized Medical Imaging and Graphics, Elsevier, 2015, 43, pp.167-178. 〈10.1016/j.compmedimag.2013.12.005〉. 〈hal-01221316v3〉
  • Pablo Mesejo. Automatic Segmentation of Anatomical Structures using Deformable Models and Bio-Inspired/Soft Computing. Electronic Letters on Computer Vision and Image Analysis, ELCVIA, 2014, 13 (2), 〈http://elcvia.cvc.uab.es/article/view/612〉. 〈hal-01221335〉
  • Roberto Ugolotti, Pablo Mesejo, Samantha Zongaro, Barbara Bardoni, Gaia Berto, et al.. Visual Search of Neuropil-Enriched RNAs from Brain In Situ Hybridization Data through the Image Analysis Pipeline Hippo-ATESC. PLoS ONE, Public Library of Science, 2013, 8 (9), 〈10.1371/journal.pone.0074481〉. 〈hal-01221314〉
  • Roberto Ugolotti, Youssef S.G. Nashed, Pablo Mesejo, Spela Ivekovič, Luca Mussi, et al.. Particle Swarm Optimization and Differential Evolution for model-based object detection. Applied Soft Computing, Elsevier, 2013, 13 (6), pp.3092-3105. 〈10.1016/j.asoc.2012.11.027〉. 〈hal-01221292〉
  • Pablo Mesejo, Roberto Ugolotti, Ferdinando Di Cunto, Mario Giacobini, Stefano Cagnoni. Automatic Hippocampus Localization in Histological Images using Differential Evolution-Based Deformable. Pattern Recognition Letters, Elsevier, 2012, 34 (3), pp.299-307. 〈hal-01221303〉
  • Ana B. Porto-Pazos, Noha Veiguela, Pablo Mesejo, Marta Navarrete, Alberto Alvarellos, et al.. Artificial Astrocytes Improve Neural Network Performance. PLoS ONE, Public Library of Science, 2011, 6 (4), 〈http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0019109〉. 〈10.1371/journal.pone.0019109〉. 〈hal-01221307〉

Communication dans un congrès12 documents

  • Stéphane Lathuilière, Benoit Massé, Pablo Mesejo, Radu Horaud. Deep Reinforcement Learning for Audio-Visual Gaze Control. IROS 2018 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2018, Madrid, Spain. pp.1-8. 〈hal-01851738〉
  • Stéphane Lathuilière, Pablo Mesejo, Xavier Alameda-Pineda, Radu Horaud. DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform Mixture Model. ECCV 2018 - European Conference on Computer Vision, Sep 2018, Munich, Germany. pp.1-16. 〈hal-01851511〉
  • Stéphane Lathuilière, Rémi Juge, Pablo Mesejo, Rafael Muñoz-Salinas, Radu Horaud. Deep Mixture of Linear Inverse Regressions Applied to Head-Pose Estimation. IEEE Conference on Computer Vision and Pattern Recognition, Jul 2017, Honolulu, Hawaii, United States. IEEE, pp.7149-7157, 2017, 〈10.1109/CVPR.2017.756〉. 〈hal-01504847〉
  • Pablo Mesejo, Sandrine Saillet, Olivier David, Christian Bénar, Jan M. Warnking, et al.. Estimating Biophysical Parameters from BOLD Signals through Evolutionary-Based Optimization. 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’15), Oct 2015, Munich, Germany. Springer, 9350 (Part II), pp.528-535, 2015, Lecture Notes in Computer Science. 〈10.1007/978-3-319-24571-3_63〉. 〈hal-01221126〉
  • Andrea Valsecchi, Pablo Mesejo, Linda Marrakchi-Kacem, Stefano Cagnoni, Sergio Damas. Automatic evolutionary medical image segmentation using deformable models. 16th IEEE Congress on Evolutionary Computation (CEC’14), Jul 2014, Beijing, China. pp.97-104, 2014, 〈10.1109/CEC.2014.6900466〉. 〈hal-01221343〉
  • Toby Collins, Pablo Mesejo, Adrien Bartoli. An Analysis of Errors in Graph-Based Keypoint Matching and Proposed Solutions. 13th European Conference on Computer Vision (ECCV’14), Sep 2014, Zurich, Switzerland. 8695, pp.138-153, 2014, Computer Vision – ECCV 2014. 〈10.1007/978-3-319-10584-0_10〉. 〈hal-01221328〉
  • Roberto Ugolotti, Pablo Mesejo, Youssef S.G. Nashed, Stefano Cagnoni. GPU-Based Automatic Configuration of Differential Evolution: A Case Study. 16th Portuguese Conference on Artificial Intelligence, EPIA 2013, Sep 2013, Azores, Portugal. 8154, pp.114-125, 2013, Progress in Artificial Intelligence. 〈10.1007/978-3-642-40669-0_11〉. 〈hal-01221512〉
  • Pablo Mesejo, Stefano Cagnoni. An experimental study on the automatic segmentation of in situ hybridization-derived images. 1st International Conference on Medical Imaging using Bio-Inspired and Soft Computing (MIBISOC’13), May 2013, Brussels, Belgium. pp.153-160. 〈hal-01221613〉
  • Pablo Mesejo, Stefano Cagnoni, Alessandro Costalunga, Davide Valeriani. Segmentation of histological images using a metaheuristic-based level set approach. 15th Genetic and Evolutionary Computation Conference companion (GECCO’13), Jul 2013, Amsterdam, Netherlands. pp.1455-1462, 2013, 〈10.1145/2464576.2466808〉. 〈hal-01221602〉
  • Roberto Ugolotti, Youssef S.G. Nashed, Pablo Mesejo, Stefano Cagnoni. Algorithm configuration using GPU-based metaheuristics. 15th Genetic and Evolutionary Computation Conference companion (GECCO’13), Jul 2013, Amsterdam, Netherlands. pp.221-222, 2013, 〈10.1145/2464576.2464682〉. 〈hal-01221570〉
  • Youssef S.G. Nashed, Pablo Mesejo, Roberto Ugolotti, Jérémie Dubois-Lacoste, Stefano Cagnoni. A Comparative Study of Three GPU-Based Metaheuristics. 12th International Conference on Parallel Problem Solving from Nature (PPSN’12), Sep 2012, Taormina, Italy. pp.398-407, 2012, 〈10.1007/978-3-642-32964-7_40〉. 〈hal-01221645〉
  • Pablo Mesejo, Roberto Ugolotti, Ferdinando Di Cunto, Stefano Cagnoni, Mario Giacobini. Automatic segmentation of hippocampus in histological images of mouse brains using deformable models and random forest. 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS’12), Jun 2012, Rome, Italy. pp.1-4, 2012, 〈10.1109/CBMS.2012.6266318〉. 〈hal-01221660〉

Chapitre d'ouvrage1 document

  • Carlos Fernandez-Lozano, Jose A. Seoane, Pablo Mesejo, Youssef S.G. Nashed, Stefano Cagnoni, et al.. Texture Classification of Proteins Using Support Vector Machines and Bio-inspired Metaheuristics. Biomedical Engineering Systems and Technologies, 452, pp.117-130, 2014, 978-3-662-44485-6. 〈10.1007/978-3-662-44485-6_9〉. 〈hal-01221496〉

Pré-publication, Document de travail1 document

  • Stéphane Lathuilière, Pablo Mesejo, Xavier Alameda-Pineda, Radu Horaud. A Comprehensive Analysis of Deep Regression. Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence. 2018. 〈hal-01754839〉

Thèse1 document

  • Pablo Mesejo. AUTOMATIC SEGMENTATION OF ANATOMICAL STRUCTURES USING DEFORMABLE MODELS AND BIO-INSPIRED/SOFT COMPUTING. Artificial Intelligence [cs.AI]. University of Parma, 2014. English. 〈tel-01363683〉