Daniel Esser
Daniel Esser
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Titel
Zitiert von
Zitiert von
Jahr
Intellix - End-User Trained Information Extraction for Document Archiving
D Schuster, K Muthmann, D Esser, A Schill, M Berger, C Weidling, ...
Document Analysis and Recognition (ICDAR), 2013 12th International …, 2013
262013
Automatic Indexing of Scanned Documents - a Layout-based Approach
D Esser, D Schuster, K Muthmann, M Berger, A Schill
Document Recognition and Retrieval XIX (DRR), San Francisco, CA, USA, 2012
162012
Information extraction efficiency of business documents captured with smartphones and tablets
D Esser, K Muthmann, D Schuster
Proceedings of the 2013 ACM symposium on Document engineering, 111-114, 2013
92013
Few-Exemplar Information Extraction for Business Documents
D Esser, D Schuster, K Muthmann, A Schill
16th International Conference on Enterprise Information Extraction (ICEIS …, 2014
42014
Rule-based versus training-based extraction of index terms from business documents: how to combine the results
D Schuster, M Hanke, K Muthmann, D Esser
Document Recognition and Retrieval XX 8658, 865813, 2013
42013
Selbstlernende Typklassifikation von Dokumenten für Information Retrieval im Document Management
D Esser
TU Dresden, 2010
32010
Cooperative and Fast-Learning Information Extraction from Business Documents for Document Archiving
D Esser
OTM Confederated International Conferences" On the Move to Meaningful …, 2013
22013
Modelspace - Cooperative Document Information Extraction in Flexible Hierarchies
D Schuster, D Esser, K Muthmann, A Schill
17th International Conference on Enterprise Information Extraction (ICEIS …, 2015
12015
Method, apparatus, and storage medium having computer executable instructions for processing of an electronic document
J Biffar, M Berger, C Weidling, A Hofmeier, D Esser, M Hanke
US Patent App. 14/138,396, 2014
12014
Positionsbasierte Indexdatenextraktion auf Dokumentencluster
D Esser
TU Dresden, 2011
12011
Cooperative Document Information Extraction in Flexible Hierarchies
D Schuster, D Esser, K Muthmann, A Schill
2015
Kooperative Informationsextraktion aus Geschäftsdokumenten auf Basis weniger Trainingsbeispiele
D Esser
TU Dresden, 2014
2014
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