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Jonathan Masci
Jonathan Masci
NNAISENSE SA
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Title
Cited by
Cited by
Year
Multi-column deep neural networks for image classification
D Ciregan, U Meier, J Schmidhuber
2012 IEEE conference on computer vision and pattern recognition, 3642-3649, 2012
7328*2012
Stacked convolutional auto-encoders for hierarchical feature extraction
J Masci, U Meier, D Cireşan, J Schmidhuber
Artificial Neural Networks and Machine Learning–ICANN 2011: 21st …, 2011
25462011
Geometric deep learning on graphs and manifolds using mixture model cnns
F Monti, D Boscaini, J Masci, E Rodola, J Svoboda, MM Bronstein
Proceedings of the IEEE conference on computer vision and pattern …, 2017
20892017
Flexible, high performance convolutional neural networks for image classification
DC Ciresan, U Meier, J Masci, LM Gambardella, J Schmidhuber
Twenty-second international joint conference on artificial intelligence, 2011
19962011
Geodesic convolutional neural networks on riemannian manifolds
J Masci, D Boscaini, M Bronstein, P Vandergheynst
Proceedings of the IEEE international conference on computer vision …, 2015
8612015
Learning shape correspondence with anisotropic convolutional neural networks
D Boscaini, J Masci, E Rodolą, M Bronstein
Advances in neural information processing systems 29, 2016
5922016
Fast image scanning with deep max-pooling convolutional neural networks
A Giusti, DC Cireşan, J Masci, LM Gambardella, J Schmidhuber
2013 IEEE international conference on image processing, 4034-4038, 2013
4312013
High-performance neural networks for visual object classification
DC Ciresan, U Meier, J Masci, LM Gambardella, J Schmidhuber
arXiv preprint arXiv:1102.0183 3, 2011
4102011
Steel defect classification with max-pooling convolutional neural networks
J Masci, U Meier, D Ciresan, J Schmidhuber, G Fricout
The 2012 international joint conference on neural networks (IJCNN), 1-6, 2012
3742012
Deep networks with internal selective attention through feedback connections
MF Stollenga, J Masci, F Gomez, J Schmidhuber
Advances in neural information processing systems 27, 2014
3212014
Flexible, high performance convolutional neural networks for image classification
DC Cireşan, U Meier, J Masci, LM Gambardella, J Schmidhuber
Proceedings of the Twenty-Second International Joint Conference on …, 2011
2442011
Learning class‐specific descriptors for deformable shapes using localized spectral convolutional networks
D Boscaini, J Masci, S Melzi, MM Bronstein, U Castellani, ...
Computer graphics forum 34 (5), 13-23, 2015
2402015
Compete to compute
RK Srivastava, J Masci, S Kazerounian, F Gomez, J Schmidhuber
Advances in neural information processing systems 26, 2013
2382013
Deep graph matching consensus
M Fey, JE Lenssen, C Morris, J Masci, NM Kriege
arXiv preprint arXiv:2001.09621, 2020
2202020
Multimodal similarity-preserving hashing
J Masci, MM Bronstein, AM Bronstein, J Schmidhuber
IEEE transactions on pattern analysis and machine intelligence 36 (4), 824-830, 2013
2182013
Learning to detect objects with a 1 megapixel event camera
E Perot, P De Tournemire, D Nitti, J Masci, A Sironi
Advances in Neural Information Processing Systems 33, 16639-16652, 2020
1732020
Anisotropic diffusion descriptors
D Boscaini, J Masci, E Rodolą, MM Bronstein, D Cremers
Computer Graphics Forum 35 (2), 431-441, 2016
1432016
A fast learning algorithm for image segmentation with max-pooling convolutional networks
J Masci, A Giusti, D Ciresan, G Fricout, J Schmidhuber
2013 IEEE international conference on image processing, 2713-2717, 2013
832013
Two-stage peer-regularized feature recombination for arbitrary image style transfer
J Svoboda, A Anoosheh, C Osendorfer, J Masci
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
762020
Matching deformable objects in clutter
L Cosmo, E Rodola, J Masci, A Torsello, MM Bronstein
2016 Fourth international conference on 3D vision (3DV), 1-10, 2016
702016
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Articles 1–20