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20052019
most citedLeaf Identification Using a Deep Convolutional Neural Network

8 citations · 13 across the 3 of their papers we have counts for

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Showing 2017 · cs.CVShow all

5 papers · 2 filters

cs.CV2017

Transfer Learning for OCRopus Model Training on Early Printed Books

Christian Reul, Christoph Wick, Uwe Springmann +1

A method is presented that significantly reduces the character error rates for OCR text obtained from OCRopus models trained on early printed books when only small amounts of diplo…

cs.CV2017★ 8 cited

Leaf Identification Using a Deep Convolutional Neural Network

Christoph Wick, Frank Puppe

Convolutional neural networks (CNNs) have become popular especially in computer vision in the last few years because they achieved outstanding performance on different tasks, such…

cs.CV2017

Improving OCR Accuracy on Early Printed Books by utilizing Cross Fold Training and Voting

Christian Reul, Uwe Springmann, Christoph Wick +1

In this paper we introduce a method that significantly reduces the character error rates for OCR text obtained from OCRopus models trained on early printed books. The method uses a…

cs.CV2017

Fully Convolutional Neural Networks for Page Segmentation of Historical Document Images

Christoph Wick, Frank Puppe

We propose a high-performance fully convolutional neural network (FCN) for historical document segmentation that is designed to process a single page in one step. The advantage of…

cs.CV2017★ 4 cited

LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed Books

Christian Reul, Uwe Springmann, Frank Puppe

A semi-automatic open-source tool for layout analysis on early printed books is presented. LAREX uses a rule based connected components approach which is very fast, easily comprehe…