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Reading and Learning: Adaptive Content Recognition (Lecture Notes in Computer Science, 2956, Band 2956) - Softcover

 
9783540219040: Reading and Learning: Adaptive Content Recognition (Lecture Notes in Computer Science, 2956, Band 2956)
Softcover
ISBN 10: 3540219048 ISBN 13: 9783540219040
Verlag: Springer, 2008

Inhaltsangabe

The amounts of information that are ?ooding people both at the workplace and in private life have increased dramatically in the past ten years. The number of paper documents doubles every four years, and the amount of information stored on all data carriers every six years. New knowledge, however, increases at a considerably lower rate. Possibilities for automatic content recognition in various media and for the processing of documents are therefore becoming more important every day. Especially in economic terms, the e?cient handling of information, i.e., ?- ing the right information at the right time, is an invaluable resource for any enterprise, but it is particularly important for small- and medium-sized ent- prises. The market for document management systems, which in Europe had a volume of approximately 5 billion euros in 2000, will increase considerably over the next few years. The BMBF recognized this development at an early stage. As early as in 1995, it pooled national capabilities in this ?eld in order to support research on the automatic processing of information within the framework of a large collaborative project (READ) involving both industrial companies and research centres. Evaluation of the results led to the conclusion that research work had been successful, and, in a second phase, funding was provided for the colla- rative follow-up project Adaptive READ from 1999 to 2003. The completion of thesetwoimportantlong-termresearchprojectshascontributedsubstantiallyto improving the possibilities of content recognition and processing of handwritten, printed and electronic documents.

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Über die Autorinnen und Autoren

Muhammad Nabeel Asim is a Senior Researcher at the German Research Center for Artificial Intelligence (DFKI) and a co-founder of intelligentX. He earned his Ph.D. with summa cum laude distinction from Technische Universität Kaiserslautern, Germany, where his research focused on developing an AI-driven framework capable of generating innovative predictive pipelines for genomics, proteomics, and multi-omics data analysis. Nabeel has an extensive publication record in areas such as DNA, RNA, and protein sequence analysis. Beyond genomics, he has applied his expertise in artificial intelligence to create diverse real-world solutions across various domains, including natural language processing, energy, and network security. Currently, he is committed to mentoring future researchers and developing innovative AI solutions to address critical global challenges.Sheraz Ahmed is a Principal Researcher at the German Research Center for Artificial Intelligence (DFKI) while running DeepReader GmbH, a company he founded to bridge the gap between academic research and industry applications. He earned his Ph.D. from Technische Universität Kaiserslautern, Germany, focusing on innovative approaches to breaking down and understanding information in document images. His work has increasingly turned toward the Life Sciences, where he sees AI as a powerful tool for accelerating scientific breakthroughs. He is also dedicated to advancing trustworthy AI, ensuring that AI technologies are ethical, transparent, and reliable for widespread adoption. In recognition of his outstanding ocontributions, Sheraz was honored with the prestigious DFKI Research Fellow Award, highlighting his leadership in the field of artificial intelligence. Multiple research stays backed by prestigious JSPS and DAAD fellowships, have shaped his international outlook on AI development. Today, he continues to explore new frontiers in AI while mentoring the next generation of researchers and building practical solutions for real-world challenges.Andreas Dengel is a professor at the Department of Computer Science at the University of Kaiserslautern-Landau, a co-founder of intelligentX as well as the Executive Director of DFKI in Kaiserslautern. Since 2009, he has held another professorship (kyakuin) at the Department of Computer Science and Intelligent Systems at Osaka Metropolitan University, with the right to teach and examine. At this university, he was also appointed Distinguished Honorary Professor (tokubetu eiyo kyoju) in March 2018, an honor bestowed on only five researchers in 135 years. He has received many honors for his work and scientific achievements. In 2019 he was selected by a jury on behalf of the German Federal Ministry of Education and Research (BMBF) as one of the most influential scientists in 50 years of AI history in Germany for his research in the field of document analysis. He is the recipient of the Order of Merit of Rhineland-Palatinate and was awarded the The Order of the Rising Sun, Gold Rays with Neck Ribbon in 2021, Japan's oldest order, on behalf of His Majesty Emperor Naruhito. Andreas Dengel has chaired numerous international conferences and is a member of the editorial boards of international journals and book series. He has written or edited 14 books and is the author of more than 600 peer-reviewed scientific publications, many of which have received the Best Paper Award. His main research areas are machine learning, pattern recognition, quantified learning, data mining, and neuro-symbolic AI. Markus Junker hat Mathematik in Mainz und Paris studiert und in mathematischer Logik promoviert. Er ist Privatdozent an der Albert-Ludwigs-Universität Freiburg.

Prof. Dr. Andreas Dengel ist Wissenschaftlicher Direktor am Deutschen Forschungszentrum für Künstliche Intelligenz (DFKI) in Kaiserslautern, Professor für Informatik an der Technischen Universität Kaiserslautern und Honorarprofessor am Dept. of Computer Science and Intelligent Systems der Graduate School of Engineering an der Osaka Prefecture University und arbeitet mit seiner Gruppe seit vielen Jahren auf dem Gebiet Semantischer Technologien.

Von der hinteren Coverseite

The amounts of information that are ?ooding people both at the workplace and in private life have increased dramatically in the past ten years. The number of paper documents doubles every four years, and the amount of information stored on all data carriers every six years. New knowledge, however, increases at a considerably lower rate. Possibilities for automatic content recognition in various media and for the processing of documents are therefore becoming more important every day. Especially in economic terms, the e?cient handling of information, i.e., ?- ing the right information at the right time, is an invaluable resource for any enterprise, but it is particularly important for small- and medium-sized ent- prises. The market for document management systems, which in Europe had a volume of approximately 5 billion euros in 2000, will increase considerably over the next few years. The BMBF recognized this development at an early stage. As early as in 1995, it pooled national capabilities in this ?eld in order to support research on the automatic processing of information within the framework of a large collaborative project (READ) involving both industrial companies and research centres. Evaluation of the results led to the conclusion that research work had been successful, and, in a second phase, funding was provided for the colla- rative follow-up project Adaptive READ from 1999 to 2003. The completion of thesetwoimportantlong-termresearchprojectshascontributedsubstantiallyto improving the possibilities of content recognition and processing of handwritten, printed and electronic documents.

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Verlag
Springer
Erscheinungsdatum
2008
Sprache
Englisch
ISBN 10 
3540219048
ISBN 13 
9783540219040
Einband
Taschenbuch
Anzahl der Seiten
368
Herausgeber
Dengel Andreas, Junker Markus, Weisbecker Anette
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