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    Aitor Alvarez-Gila

    Aitor Alvarez-Gila

    Computer vision and deep learning scientist. Lead researcher at Tecnalia. Photographer (not really)

    • Bilbao, Spain
    • Computer Vision at Tecnalia
    • LAMP team at CVC/UAB
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    Tecnalia’s deep learning-based Surface Inspection system SURFIN featured in Vision Systems Design

    less than 1 minute read

    surfin Tecnalia’s surface inspection system for hot long metal products SURFIN is migrating to a deep learning-based solution using Convolutional Neural Networks, and the December 2016 issue of Vision Systems Design includes an article on it with some design and performance details.

    References:

    A. Cruz-Lopez, A. Lago, R. Gonzalez, A. Alvarez-Gila, and J. A. Gutiérrez Olabarria, “High-speed inspection system finds defects in steel,” Vision Systems Design, no. December 2016-1, pp. 24–27, Dec-2016.

    A. Alvarez-Gila, A. Lopez-Cruz, S. Rodriguez-Vaamonde, M. Linares, J. A. Gutierrez-Olabarria, and E. Garrote, “Deep Convolutional Neural Networks for surface quality inspection of hot long metal products,” presented at the First European Machine Vision Forum, Heidelberg, Germany, 2016.

    Tags: cnn, deep learning, surfin, tecnalia

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    PhD defended!

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    Published: July 26, 2022

    Last Tuesday, July 19th 2022, I successfully defended my PhD dissertation at CVC (Barcelona), obtaining an Excellent Cum Laude grade. The thesis is titled “Self-supervised learning for image-to-image translation in the small data regime” and was developed at Computer Vision Center’s Learning And Machine Perception (LAMP) team and Tecnalia, under the supervision of Joost van de Weijer and Estibaliz Garrote. Many thanks to both!

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    Invited talk on deep learning at the Faculty of Science and Technology (UPV/EHU)

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    Published: September 20, 2019

    Next Wednesday, October 2nd, I’ll be giving an introductory talk to Deep Learning techniques at the Faculty of Science and Technology of the University of the Basque Country (UPV/EHU).

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    New journal paper on synthetic image blurring for self-supervised deep blur detection

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    Published: August 25, 2019

    Our paper “Self-Supervised Blur Detection from Synthetically Blurred Scenes” just got accepted for publication at the Image and Vision Computing journal (Q1).

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    PLOS ONE paper on deep learning techniques for the detection of lethal ventricular arrhythmia on out-of-hospital cardiac arrest patients

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    Published: May 20, 2019

    Our paper “Mixed Convolutional and Long Short-Term Memory Network for the Detection of Lethal Ventricular Arrhythmia” was just published on PLOS ONE.

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