25 citations · 29 across the 3 of their papers we have counts for
3 papers
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…
A Pitfall of Unsupervised Pre-Training
Michele Alberti, Mathias Seuret, Rolf Ingold +1
The point of this paper is to question typical assumptions in deep learning and suggest alternatives. A particular contribution is to prove that even if a Stacked Convolutional Aut…
Historical Document Image Segmentation with LDA-Initialized Deep Neural Networks
Michele Alberti, Mathias Seuret, Vinaychandran Pondenkandath +2
In this paper, we present a novel approach to perform deep neural networks layer-wise weight initialization using Linear Discriminant Analysis (LDA). Typically, the weights of a de…