223 citations · 243 across the 5 of their papers we have counts for
6 papers
Learning shape correspondence with anisotropic convolutional neural networks
Davide Boscaini, Jonathan Masci, Emanuele Rodolà +1
Establishing correspondence between shapes is a fundamental problem in geometry processing, arising in a wide variety of applications. The problem is especially difficult in the se…
A Fast Learning Algorithm for Image Segmentation with Max-Pooling Convolutional Networks
Jonathan Masci, Alessandro Giusti, Dan Cireşan +2
We present a fast algorithm for training MaxPooling Convolutional Networks to segment images. This type of network yields record-breaking performance in a variety of tasks, but is…
A Learning Framework for Morphological Operators using Counter-Harmonic Mean
Jonathan Masci, Jesús Angulo, Jürgen Schmidhuber
We present a novel framework for learning morphological operators using counter-harmonic mean. It combines concepts from morphology and convolutional neural networks. A thorough ex…
Object Recognition with Multi-Scale Pyramidal Pooling Networks
Jonathan Masci, Ueli Meier, Gabriel Fricout +1
We present a Multi-Scale Pyramidal Pooling Network, featuring a novel pyramidal pooling layer at multiple scales and a novel encoding layer. Thanks to the former the network does n…
Multimodal similarity-preserving hashing
Jonathan Masci, Michael M. Bronstein, Alexander A. Bronstein +1
We introduce an efficient computational framework for hashing data belonging to multiple modalities into a single representation space where they become mutually comparable. The pr…
High-Performance Neural Networks for Visual Object Classification
Dan C. Cireşan, Ueli Meier, Jonathan Masci +2
We present a fast, fully parameterizable GPU implementation of Convolutional Neural Network variants. Our feature extractors are neither carefully designed nor pre-wired, but rathe…