Mots-clés

Nombre de documents

22

Pablo Mesejo


My name is Pablo Mesejo Santiago and I hold a starting researcher position at INRIA (France), one of the top institutions in computer science and mathematics. My current work is mainly related with the integration of deep learning into probabilistic generative models for visual and audio recognition.

My principal areas of interest are computer vision and bio-inspired/soft computing methods, as well as their application to real-world problems in biomedical image/signal processing and analysis. Typical tools I use in my research are evolutionary computation methods, artificial neural networks, ensemble learning, and image segmentation and registration algorithms, eventually bridging the gap to the practitioners. Also, one of my main research interests is to understand stochastic optimization algorithms in continuous search spaces, focusing about whether and how they are useful in practice.

More information about me and my publications can be found in the following links: personal webpage, Google Scholar, ORCID, Linkedin, Universidade da Coruña, Università degli Studi di Parma, DBLP, ResearchGate and ResearcherID.


Article dans une revue10 documents

  • 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, 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, 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, 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, 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〉
  • 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〉
  • 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 congrès10 documents

  • 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. 〈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〉
  • 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〉
  • 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〉
  • 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, 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, 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〉
  • 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〉

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, Benoît Massé, Pablo Mesejo, Radu Horaud. Neural Network Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction. 14 pages. 2017. 〈hal-01643775〉