International audienceThe work reported in this paper aims at performance optimization in the digitization of documents pertaining to the cultural heritage domain. A hybrid method is roposed, combining statistical classification algorithms and linguistic knowledge to automatize post-OCR error detection and correction. The current paper deals with the integration of linguistic modules and their impact on error detection
Optical character recognition (OCR) for historical documents is a complex procedure subject to a uni...
Optical character recognition (OCR) for historical documents is a complex procedure subject to a uni...
This work focuses on the assessment of characters recognition results produced automatically by opti...
International audienceThe work reported in this paper aims at performance optimization in the digiti...
International audienceThe work reported in this paper aims at performance optimization in the digiti...
International audienceThe work reported in this paper aims at performance optimization in the digiti...
A trend to digitize historical paper-based archives has emerged in recent years, with the advent of ...
A trend to digitize historical paper-based archives has emerged in recent years, with the advent of ...
A trend to digitize historical paper-based archives has emerged in recent years, with the advent of ...
For indexing the content of digitized historical texts, optical character recognition (OCR) errors a...
For indexing the content of digitized historical texts, optical character recognition (OCR) errors a...
Born-analog documents contain enormous knowledge which is valuable to our society. For the purpose o...
In this paper we describe our efforts in reducing and correcting OCR errors in the context of buildi...
International audienceThis paper describes the second round of the ICDAR 2019 competition on post-OC...
International audienceThe French National Library (BnF ) has launched many mass digitization project...
Optical character recognition (OCR) for historical documents is a complex procedure subject to a uni...
Optical character recognition (OCR) for historical documents is a complex procedure subject to a uni...
This work focuses on the assessment of characters recognition results produced automatically by opti...
International audienceThe work reported in this paper aims at performance optimization in the digiti...
International audienceThe work reported in this paper aims at performance optimization in the digiti...
International audienceThe work reported in this paper aims at performance optimization in the digiti...
A trend to digitize historical paper-based archives has emerged in recent years, with the advent of ...
A trend to digitize historical paper-based archives has emerged in recent years, with the advent of ...
A trend to digitize historical paper-based archives has emerged in recent years, with the advent of ...
For indexing the content of digitized historical texts, optical character recognition (OCR) errors a...
For indexing the content of digitized historical texts, optical character recognition (OCR) errors a...
Born-analog documents contain enormous knowledge which is valuable to our society. For the purpose o...
In this paper we describe our efforts in reducing and correcting OCR errors in the context of buildi...
International audienceThis paper describes the second round of the ICDAR 2019 competition on post-OC...
International audienceThe French National Library (BnF ) has launched many mass digitization project...
Optical character recognition (OCR) for historical documents is a complex procedure subject to a uni...
Optical character recognition (OCR) for historical documents is a complex procedure subject to a uni...
This work focuses on the assessment of characters recognition results produced automatically by opti...