51 citations · 142 across the 16 of their papers we have counts for
5 papers · 1 filter
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…
Open Evaluation Tool for Layout Analysis of Document Images
Michele Alberti, Manuel Bouillon, Rolf Ingold +1
This paper presents an open tool for standardizing the evaluation process of the layout analysis task of document images at pixel level. We introduce a new evaluation tool that is…
Historical Document Image Segmentation with LDA-Initialized Deep Neural Networks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…
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…
PCA-Initialized Deep Neural Networks Applied To Document Image Analysis
Mathias Seuret, Michele Alberti, Rolf Ingold +1
In this paper, we present a novel approach for initializing deep neural networks, i.e., by turning PCA into neural layers. Usually, the initialization of the weights of a deep neur…