Part 7: Deep Learning - Convolutional ANNInternational audienceThis paper presents an overview of training strategies for optical character recognition of historical documents. The main issue is the lack of the annotated data and its quality. We summarize several ways of synthetic data preparation. The main goal of this paper is to show and compare possibilities how to train a convolutional recurrent neural network classifier using the synthetic data and its combination with a real annotated dataset
This work deals with the creation of a system that allows uploading and annotating scans of historic...
This thesis summarises the research-oriented study of applicability of Long Short-Term Memory Recurr...
The digitization of historical handwritten document images is important for the preservation of cult...
Part 7: Deep Learning - Convolutional ANNInternational audienceThis work aims at data preparation fo...
This paper presents an overview of training strategies for optical character recognition of historic...
The aim of this work is to create a system for historical documents classification . The task is spe...
In this paper a complete OCR methodology for recognizing historical documents, either printed or han...
Automatic analysis of scanned historical documents comprises a wide range of image analysis tasks, w...
Abstract. The need for accessing information through the web and other kind of distributed media mak...
Historical manuscripts are the main source of information about past. In recent years, digitization ...
In spite of the improvement of Commercial Optical Character Recognition (OCR) during the last years,...
Historical documents are a valuable source of cultural knowledge and can provide information about p...
The aim of this Master's thesis is to design and implement an OCR system for archival historical doc...
This thesis deals with text line recognition of historical documents. Historical texts dating back t...
Preserving historical archival heritage involves not only physical measures to safeguard these valua...
This work deals with the creation of a system that allows uploading and annotating scans of historic...
This thesis summarises the research-oriented study of applicability of Long Short-Term Memory Recurr...
The digitization of historical handwritten document images is important for the preservation of cult...
Part 7: Deep Learning - Convolutional ANNInternational audienceThis work aims at data preparation fo...
This paper presents an overview of training strategies for optical character recognition of historic...
The aim of this work is to create a system for historical documents classification . The task is spe...
In this paper a complete OCR methodology for recognizing historical documents, either printed or han...
Automatic analysis of scanned historical documents comprises a wide range of image analysis tasks, w...
Abstract. The need for accessing information through the web and other kind of distributed media mak...
Historical manuscripts are the main source of information about past. In recent years, digitization ...
In spite of the improvement of Commercial Optical Character Recognition (OCR) during the last years,...
Historical documents are a valuable source of cultural knowledge and can provide information about p...
The aim of this Master's thesis is to design and implement an OCR system for archival historical doc...
This thesis deals with text line recognition of historical documents. Historical texts dating back t...
Preserving historical archival heritage involves not only physical measures to safeguard these valua...
This work deals with the creation of a system that allows uploading and annotating scans of historic...
This thesis summarises the research-oriented study of applicability of Long Short-Term Memory Recurr...
The digitization of historical handwritten document images is important for the preservation of cult...