作者: Thomas Plötz , Gernot A. Fink
DOI: 10.1007/978-1-4471-2188-6_5
关键词: Computer science 、 Research groups 、 Key features 、 Data science 、 Sample (statistics) 、 Experimental science 、 Key (cryptography) 、 Handwriting recognition 、 Field (computer science)
摘要: Aiming at a comprehensive overview of Markov-model based handwriting recognition this chapter focusses on the description systems for practical applications. After theoretical aspects and key developments in field have been surveyed, integration concrete evaluations capabilities are discussed. The starts with most relevant data-sets. As usual all experimental science, research relies availability high-quality sample data training evaluation purposes. According to general shift efforts from online offline recognition, majority described current literature is dedicated recognition. Reviewing literature, we identified seven major systems. We concentrated those that still being maintained further developed. In their features will be performance figures given.