Ph.D.

OLARIK SURINTA

Multi-agent Intelligent Simulation Laboratory (MISL) Research Unit, Department of Information Technology, Faculty of Informatics, Mahasarakham University, THAILAND

email: olarik.s@msu.ac.th
CV: download
profile: scopus, loopgoogle scholar, ResearchGate

ORCID iD iconhttps://orcid.org/0000-0002-0644-1435

 Olarik Surinta grew up in Chiang Mai, Thailand and received his BBA from Rajamangala Institute of Technology and his MSc from King Mongkut’s Institute of Technology North Bangkok. He started his career in 2004 as a lecturer at the department of information technology in the faculty of informatics, Mahasarakham University. Since 2011, he has been promoted to assistant professor. In 2016, he graduated Ph.D. at University of Groningen, Institute of Artificial Intelligence and Cognitive Engineering (ALICE) under the supervision of Prof. dr. Lambert Schomaker and Dr. Marco Wiering

Education


PhD, 2016 , Artificial Intelligence and Cognitive Engineering, University of Groningen

MSc, 2003, Information Technology, King Mongkut’s Institute of Technology North Bangkok

BBA, 1999, Information Systems, Rajamangala Institute of Technology

Research Interests


  • Deep learning
  • Artificial intelligence
  • Machine learning
  • Computer vision & Image processing
  • Handwritten recognition
    • Document layout analysis
    • Handwritten word/character recognition
    • Word spotting


Multi-Script Handwritten Character Recognition using Feature Descriptors and Machine Learning

Dissertation: Multi-Script Handwritten Character Recognition using Feature Descriptors and Machine Learning

Promotor: Prof. dr. Lambert R.B. Schomaker
Supervisor: Asst.prof. dr. Marco A. Wiering

There exists no generic method for recognizing handwritten scripts from different writing systems, cultures or historical periods. Asian scripts pose a number of interesting fundamental problems at the levels of image processing, text segmentation, feature extraction, shape classification and language modeling. Instead of spending human efforts at each of these level, the current challenge is to exploit machine learning methods. The main objective of the project is to automatically recognize handwritten Thai and to automatically convert documents written in Thai to text files.

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MULTI-AGENT INTELLIGENT SIMULATION LABORATORY (MISL) RESEARCH UNIT

 

Department of Information Technology, Faculty of Informatics, Mahasarakham University, Thailand