51 citations · 142 across the 16 of their papers we have counts for
6 papers · 1 filter
Trainable Spectrally Initializable Matrix Transformations in Convolutional Neural Networks
Michele Alberti, Angela Botros, Narayan Schuez +3
In this work, we investigate the application of trainable and spectrally initializable matrix transformations on the feature maps produced by convolution operations. While previous…
Labeling, Cutting, Grouping: an Efficient Text Line Segmentation Method for Medieval Manuscripts
Michele Alberti, Lars Vögtlin, Vinaychandran Pondenkandath +3
This paper introduces a new way for text-line extraction by integrating deep-learning based pre-classification and state-of-the-art segmentation methods. Text-line extraction in co…
Graph-Based Offline Signature Verification
Paul Maergner, Nicholas R. Howe, Kaspar Riesen +2
Graphs provide a powerful representation formalism that offers great promise to benefit tasks like handwritten signature verification. While most state-of-the-art approaches to sig…
Improving Reproducible Deep Learning Workflows with DeepDIVA
Michele Alberti, Vinaychandran Pondenkandath, Lars Vögtlin +3
The field of deep learning is experiencing a trend towards producing reproducible research. Nevertheless, it is still often a frustrating experience to reproduce scientific results…
Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game Jass
Joel Niklaus, Michele Alberti, Vinaychandran Pondenkandath +2
In the last decades we have witnessed the success of applications of Artificial Intelligence to playing games. In this work we address the challenging field of games with hidden in…
A Comprehensive Study of ImageNet Pre-Training for Historical Document Image Analysis
Linda Studer, Michele Alberti, Vinaychandran Pondenkandath +5
Automatic analysis of scanned historical documents comprises a wide range of image analysis tasks, which are often challenging for machine learning due to a lack of human-annotated…