Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-35725-1_29
Title: A novel and robust system for time recognition of the digital video clock using the domain knowledge
Authors: Yu, X.
Rong, T.
Li, N.
Leong, H.W. 
Keywords: Digital Video Clock
Mixture Gaussian
On-the-fly SVM
Second Periodicity
Time Recognition
Issue Date: 2013
Source: Yu, X.,Rong, T.,Li, N.,Leong, H.W. (2013). A novel and robust system for time recognition of the digital video clock using the domain knowledge. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7732 LNCS (PART 1) : 318-326. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-35725-1_29
Abstract: This paper presents a novel and robust system for recognizing the time of the digital video clock by using the domain knowledge. This system comprises a set of the functions for the time recognition so that the user can conveniently use these functions to recognize the time of digital video clocks or to execute some steps of recognizing time. These functions are novel and robust because they use the novel methods derived from the domain knowledge of the digital video clock. These methods are region second periodicity, global maximum model, digit location model, digit-sequence recognition, and on-thefly SVM. Experimental results show that both the functions and the system can achieve very high recognition accuracy. © Springer-Verlag 2013.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/77969
ISBN: 9783642357244
ISSN: 03029743
DOI: 10.1007/978-3-642-35725-1_29
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