publications

 

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2021

  • Svanera, M., Benini, S., Bontempi, D., & Muckli, L. (2021). CEREBRUM-7T: Fast and Fully-volumetric Brain Segmentation of 7 Tesla MR Volumes. Human Brain Mapping (link).
  • Svanera, M., Morgan, A., Petro, L., Muckli, L. (2021). A Self-Supervised Deep Neural Network for Image Completion Resembles Early Visual Cortex fMRI Activity Patterns for Occluded Scenes. Journal of Vision (link).

2020

  • Svanera, M., Benini, S., Bontempi, D., & Muckli, L. (2020). CEREBRUM 7T: Fast and Fully-volumetric Brain Segmentation of 7 Tesla MR Volumes. bioRxiv (link).
  • Svanera, M., Morgan, A., Petro, L., Muckli, L. (2020). A Self-Supervised Deep Neural Network for Image Completion Resembles Early Visual Cortex fMRI Activity Patterns for Occluded Scenes. (link).
  • Bontempi, D., Benini, S., Signoroni, A., Svanera*, M., & Muckli*, L. (2020). CEREBRuM: a Convolutional Encoder-decodeR for Fully Volumetric Fast sEgmentation of BRain MRI. Medical Imaging Analysis (link).
  • Svanera, M., S. Benini, D. Bontempi, A. Fracasso, L. Muckli, “Fast brain segmentation of out-of-the-scanner MR 7T volumes using deep learning”, in Annual Meeting of the Organization for Human Brain Mapping (OHBM 2020), Montreal, Canada, June 26-30, 2020. (poster)

2019

  • Kovács, A. B., Raz, G., Valente, G., Svanera, M., & Benini, S. (2019). A Robust Neural Fingerprint of Cinematic Shot-Scale. Projections13(3), 23-52 (link).
  • Bontempi, D., Benini, S., Signoroni, A., Svanera*, M., & Muckli*, L. (2019). CEREBRuM: a Convolutional Encoder-decodeR for Fully Volumetric Fast sEgmentation of BRain MRI. arXiv preprint arXiv:1909.05085 (link).
  • Svanera, M., Savardi, M., Signoroni, A., Kovács, A. B., & Benini, S. (2019). Who is the film’s director? Authorship recognition based on shot features. IEEE MultiMedia (link).
  • Svanera, M., Savardi, M., Benini, S., Signoroni, A., Raz, G., Hendler, T., R. Goebel, & Valente, G. (2019). Transfer learning of deep neural network representations for fMRI decoding. Journal of Neuroscience Methods (link).
  • Bontempi, D., S. Benini, A. Signoroni, L. Muckli*, and Svanera M.*. “Fast Brain MRI Segmentation Using a Volumetric Deep Learning Approach”. In: 2019 Conference on Cognitive Computational Neuroscience (CCN) (link).

2018

  • Svanera, M., Savardi, M., Signoroni, A., Kovács, A. B., & Benini, S. (2018). Who is the director of this movie? Automatic style recognition based on shot features. arXiv preprint arXiv:1807.09560 (link).
  • Muhammad, U. R., Svanera, M., Leonardi, R., & Benini, S. (2018). Hair detection, segmentation, and hairstyle classification in the wild. Image and Vision Computing71, 25-37 (link).
  • Svanera M., A. T. Morgan, L. S. Petro, and L. Muckli. “Unsupervised deep neural network for fMRI feedback modelling”. In: 2018 Conference on Cognitive Computational Neuroscience (CCN). (link).

2017

  • Raz, G., Svanera, M., Singer, N., Gilam, G., Cohen, M. B., Lin, T., … & Goebel, R. (2017). Robust inter-subject audiovisual decoding in functional magnetic resonance imaging using high-dimensional regression. Neuroimage163, 244-263 (link).
  • Svanera, M., Benini, S., Raz, G., Hendler, T., Goebel, R., & Valente, G. (2017). Deep driven fMRI decoding of visual categories. arXiv preprint arXiv:1701.02133 (link).

2016

  • Benini, S., Svanera, M., Adami, N., Leonardi, R., & Kovács, A. B. (2016). Shot scale distribution in art films. Multimedia Tools and Applications75(23), 16499-16527 (link).
  • Svanera, M., Muhammad, U. R., Leonardi, R., & Benini, S. (2016, September). Figaro, hair detection and segmentation in the wild. In 2016 IEEE International Conference on Image Processing (ICIP) (pp. 933-937). IEEE (link).
  • Gordiychuk, A., Svanera, M., Benini, S., & Poesio, P. (2016). Size distribution and Sauter mean diameter of micro bubbles for a Venturi type bubble generator. Experimental Thermal and Fluid Science70, 51-60 (link).

2015

  • Svanera, M., Benini, S., Adami, N., Leonardi, R., & Kovács, A. B. (2015, June). Over-the-shoulder shot detection in art films. In 2015 13th International Workshop on Content-Based Multimedia Indexing (CBMI) (pp. 1-6). IEEE (link).