96 citations · 265 across the 23 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…
Historical Document Image Segmentation with LDA-Initialized Deep Neural Networks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…
Convolutional Neural Networks for Page Segmentation of Historical Document Images
Kai Chen, Mathias Seuret
This paper presents a Convolutional Neural Network (CNN) based page segmentation method for handwritten historical document images. We consider page segmentation as a pixel labelin…
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…