Pablo Mesejo Santiago
2
Documents
Présentation
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](http://www.shanghairanking.com/Shanghairanking-Subject-Rankings/computer-science-engineering.html).
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: [Google Scholar](https://scholar.google.com/citations?user=dUlIWxcAAAAJ), [ORCID](http://orcid.org/0000-0001-9955-2101), [Linkedin](https://fr.linkedin.com/pub/pablo-mesejo-santiago/54/348/71b/en), [DBLP](http://dblp.uni-trier.de/pers/hd/m/Mesejo:Pablo), [ResearchGate](https://www.researchgate.net/profile/Pablo_Mesejo) and [ResearcherID](http://www.researcherid.com/ProfileView.action?SID=V24kpAPPEKmBvYjOeqa&returnCode=ROUTER.Success&queryString=KG0UuZjN5WkwsNoH4O%252BEmmn%252FPULU3%252FDZxELZtBub7fk%253D&SrcApp=CR&Init=Yes).
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](http://www.shanghairanking.com/Shanghairanking-Subject-Rankings/computer-science-engineering.html).
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: [Google Scholar](https://scholar.google.com/citations?user=dUlIWxcAAAAJ), [ORCID](http://orcid.org/0000-0001-9955-2101), [Linkedin](https://fr.linkedin.com/pub/pablo-mesejo-santiago/54/348/71b/en), [DBLP](http://dblp.uni-trier.de/pers/hd/m/Mesejo:Pablo), [ResearchGate](https://www.researchgate.net/profile/Pablo_Mesejo) and [ResearcherID](http://www.researcherid.com/ProfileView.action?SID=V24kpAPPEKmBvYjOeqa&returnCode=ROUTER.Success&queryString=KG0UuZjN5WkwsNoH4O%252BEmmn%252FPULU3%252FDZxELZtBub7fk%253D&SrcApp=CR&Init=Yes).
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A Comprehensive Analysis of Deep RegressionIEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, 42 (9), pp.2065-2081. ⟨10.1109/TPAMI.2019.2910523⟩
Article dans une revue
hal-01754839v1
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DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform Mixture ModelECCV 2018 - European Conference on Computer Vision, Sep 2018, Munich, Germany. pp.205-221, ⟨10.1007/978-3-030-01228-1_13⟩
Communication dans un congrès
hal-01851511v1
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