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Member Profile

This is "The Multimedia Signal Processing and Security Lab", short WaveLab, website. We are a research group at the Artificial Intelligence and Human Interfaces (AIHI) Department of the University of Salzburg led by Andreas Uhl. Our research is focused on Visual Data Processing and associated security questions. Most of our work is currently concentrated on Biometrics, Media Forensics and Media Security, Medical Image and Video Analysis, and application oriented fundamental research in digital humanities, individualised aquaculture and sustainable wood industry.
 
 Portrait Photo  
Firstname:  Eduardo
Lastname:  Ribeiro
Born: 
Room No: 0.29
Telephone: (+43) 662 8044 - 6300
Mail:  uft [dot] eduardo [at] gmail [dot] com
Homepage: 

Eduardo Ribeiro

 
 

About Me:
I am a PhD student in the WaveLab group.

 
 

Research Interests:

  • Deep Learning
  • Superresolution

 
 

Publications:

    Journal Articles

    1. [Ribeiro18a   ] Iris Super-Resolution using CNNs: is Photo-Realism Important to Iris Recognition? Eduardo Ribeiro, Andreas Uhl, Fernando Alonso-Fernandez IET Biometrics 1:8, pp. 69-78, 2018
    2. [Ribeiro16c  ] Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification Eduardo Ribeiro, Andreas Uhl, Georg Wimmer, Michael Häfner Computational and Mathematical Methods in Medicine 2016, pp. Article ID 6584725, Hindawi Publishing Corporation, 2016

    Conference Papers

    1. [Ribeiro16d  ] Exploring Texture Transfer Learning for Colonic Polyp Classification via Convolutional Neural Networks Eduardo Ribeiro, Michael Häfner, Georg Wimmer, Toro Tamaki, J.J.W. Tischendorf, S. Yoshida, S. Tanaka, Andreas Uhl In 14th International IEEE Symposium on Biomedical Imaging (ISBI'17)April 2017
    2. [Ribeiro17b  ] Exploring Texture Transfer Learning via Convolutional Neural Networks for Iris Super Resolution Eduardo Ribeiro, Andreas Uhl In Arslan Brömme, Christoph Busch, Christian Rathgeb, Andreas Uhl, editors, Proceedings of the 2017 International Conference of the Biometrics Special Interest Group (BIOSIG'17), Darmstadt, Germany 2017, LNI, GI / IEEE, 2017
    3. [Ribeiro17a  ] Exploring Deep Learning Image Super-Resolution for Iris Recognition Eduardo Ribeiro, Andreas Uhl, Fernando Alonso-Fernandez, Reuben A. Farrugia In Proc. of the 25th European Signal Processing Conference (EUSIPCO 2017), Kos Island, Greece, August 28 - September 2, 20172017
    4. [Ribeiro16b ] Transfer Learning for Colonic Polyp Classification using Off-the-Shelf CNN Features (Best Paper Award, 3rd Place) Eduardo Ribeiro, Andreas Uhl, Georg Wimmer, Michael Häfner In Proceedings of the 3rd International Workshop on Computer-Assisted and Robotic Endoscopy (CARE'16), pp. 1-13, Springer LNCS, 10170, 2016
    5. [Ribeiro16a  ] Colonic Polyp Classification with Convolutional Neural Networks Eduardo Ribeiro, Andreas Uhl, Michael Häfner In Proceedings of the 29th IEEE International Symposium on Computer-Based Medical Systems (CBMS'16), pp. 253-258, June 2016