Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Siegfried Stiehl"'
Publikováno v:
Zeitschrift für Bankrecht und Bankwirtschaft. 34:341-356
Zusammenfassung Am modernen Kapitalmarkt werden zunehmend durch Künstliche Intelligenz (KI) und maschinelles Lernen (ML) gesteuerte Algorithmen eingesetzt. Neben enormen Effizienzgewinnen ergeben sich bei den fortschrittlichsten, selbstlernenden Alg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53c62edec8a0fd02153af492b7efa129
https://doi.org/10.15375/zbb-2022-0604
https://doi.org/10.15375/zbb-2022-0604
Publikováno v:
Artificial Intelligence in Finance ISBN: 9781803926179
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::834e137f214cfcedfbda65a17955288c
https://doi.org/10.4337/9781803926179.00019
https://doi.org/10.4337/9781803926179.00019
Publikováno v:
Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::828c5c0652a61c7c1dc2934a7e8ddad8
https://doi.org/10.5220/0010801300003122
https://doi.org/10.5220/0010801300003122
Publikováno v:
Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030687861
ICPR Workshops (7)
ICPR Workshops (7)
This paper presents an interactive system for experimental ancient document analysis applied to the specific use case of the computational analysis of magical signs, called Brillenbuchstaben or charakteres, in digitized Jewish manuscripts. It draws u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::431e42f7110f5325fb9fbf7b77951b63
https://doi.org/10.1007/978-3-030-68787-8_11
https://doi.org/10.1007/978-3-030-68787-8_11
Publikováno v:
SSRN Electronic Journal.
This paper offers a novel perspective on the implications of increasingly autonomous and “black box” algorithms, within the ramification of algorithmic trading, for the integrity of capital markets. Artificial intelligence (AI) and particularly i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55752f23ec66731e2a6b78cfe191993d
https://doi.org/10.2139/ssrn.3788872
https://doi.org/10.2139/ssrn.3788872
Autor:
H. Siegfried Stiehl, Vinodh Rajan
Publikováno v:
Mensch & Computer
Recently, Visual Programming Languages (VPLs) have been applied to a wide variety of domains ranging, usually for users lacking traditional programming skills. However, there have not been yet any concrete attempts to harness VPLs in the domain of Do
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d5e0e32134054020cd82c851ad66ba04
https://doi.org/10.1145/3340764.3345372
https://doi.org/10.1145/3340764.3345372
Autor:
Vinodh Rajan, H. Siegfried Stiehl
Publikováno v:
HDI@ICDAR
The research field of Document Image Analysis (DIA) produces state-of-the-art methods that are intended to analyze digitized documents, a substantial portion of which lie in the realm of humanities. However, applying the methods, more often than not,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc5bbd90297f781f42b2638bd643d405
https://doi.org/10.1109/icdarw.2019.20048
https://doi.org/10.1109/icdarw.2019.20048
Publikováno v:
ICFHR
Several methods have been proposed for the task of writer identification for historical manuscripts. Most of these methods have been evaluated on private historical datasets only, while few have been evaluated on the recently published historical dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa7a6b4d4f51ba8a7f67c081cdb508ce
https://doi.org/10.1109/icfhr-2018.2018.00099
https://doi.org/10.1109/icfhr-2018.2018.00099
Autor:
Weickert, Joachim, Heers, Josef, Schnörr, Christoph, Zuiderveld, Karel J., Scherzer, Otmar, Siegfried Stiehl, H.
Publikováno v:
In Real-Time Imaging February 2001 7(1):31-45
Publikováno v:
ICDAR
Writer identification and verification can be viewed as a classification problem, where each writer represents a class. We propose a classifier for offline, text-independent, and segmentation-free writer identification based on the Local Naive Bayes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bd5a1b7d4b4e143c8fe0ad3a4453c87
https://doi.org/10.1109/icdar.2017.168
https://doi.org/10.1109/icdar.2017.168