JCU > Research Portfolio > Dr Art (Hemmaphan) Suwanwiwat

About

Art is an Information Technology lecturer with particular interests in in document analysis and recognition which is the subfield of Pattern Recognition and Artificial Intelligence.

She has been employing Artificial Neural Networks, Support Vector Machines, and Hidden Markov Models in her research. She is currently exploring biometric (based on signatures and name components). She is also interested in Network Security and deep learning.

Teaching

CP1402: Internet Fundamentals (Level 1; CNS & TSV)
CP1406: Web Design and Development (Level 1; CNS & TSV)
CP2408: Design Thinking II (Level 2; CNS)
CP3401: e-Strategic Management (Level 3; CNS & TSV)
CP3404: Information Security (Level 3; CNS)
CP5603: Advanced E-Security (Level 5; CNS)
CP5631: Internet Fundamentals (Level 5; CNS & TSV)
CP5636: e-Strategic Management (Level 5; CNS & TSV)
CP5638: Web Design and Development (Level 5; CNS & TSV)
CP5640: Information Management and Analytics Technology (Level 5; ONL)

Interests

Research

Document Analysis
Image Processing
Artificial Neural Networks
Support Vector Machines
Biometric

Research Disciplines

Socio-Economic Objectives

Publications

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU.

Journal Articles

Sinclair J, Suwanwiwat H and Lee I (2023) A hybrid data gathering and agent based cognitive architecture for realistic crowd simulations. Journal of Simulation, 17 (2). pp. 121-148
Sinclair J, Suwanwiwat H and Lee I (2022) A Virtual Reality and Questionnaire Approach to Gathering Real World Data for Agent Based Crowd Simulation Models. Presence: Virtual and Augmented Reality, 28. pp. 293-312
Suwanwiwat H, Das A, Saqib M and Pal U (2021) Benchmarked multi-script Thai scene text dataset and its multi-class detection solution. Multimedia Tools and Applications, 80. pp. 11843-11863
Das A, Suwanwiwat H, Ferrer M, Pal U and Blumenstein M (2018) Thai automatic signature verification system employing textural features. IET Biometrics, 7 (6). pp. 615-627

Conference Papers

Das A, Suwanwiwat H, Pal U and Blumenstein M (2020) ICFHR 2020 Competition on Short answer ASsessment and Thai student SIGnature and Name COMponents Recognition and Verification (SASIGCOM 2020). Proceedings of the 17th International Conference on Frontiers in Handwriting Recognition. In: ICFHR 2020: 17th International Conference on Frontiers in Handwriting Recognition, 8-10 September 2020, Dortmund, Germany
Suwanwiwat H, Das A, Pal U and Blumenstein M (2018) ICFHR 2018 competition on Thai student signatures and name components recognition and verification (TSNCRV2018). Proceedings of the 16th International Conference on Frontiers in Handwriting Recognition. In: ICFHR 2018: 16th International Conference on Frontiers in Handwriting Recognition, 5-8 August 2018, Niagara Falls, NY, USA
Suwanwiwat H, Das A, Ferrer M, Pal U and Blumenstein M (2018) An investigation of discrete Hidden Markov Models on handwritten short answer assessment system. Proceedings of the International Conference on Pattern Recognition and Artificial Intelligence. In: ICPRAI 2018: International Conference on Pattern Recognition and Artificial Intelligence, May 14-17 2018, Montréal, Canada
Suwanwiwat H, Das A, Ferrer M, Pal U and blumenstein M (2017) An automatic student verification system utilising off-line Thai name components. Proceedings of the International Conference on Digital Image Computing. In: DICTA 2017: International Conference on Digital Image Computing: Techniques and Applications, 29 November - 1 December 2017, Sydney, NSW, Australia
Suwanwiwat H, Pal U and Blumenstein M (2016) An investigation of novel combined features for a handwritten short answer assessment system. Proceedings of the 15th International Conference on Frontiers in Handwriting Recognition. In: ICFHR 20146: 15th International Conference on Frontiers in Handwriting Recognition, 23-26 October 2016, Shenzhen, China
Suwanwiwat H, Pal U and Blumenstein M (2016) An automatic off-line short answer assessment system using novel hybrid features. Proceedings of the International Conference on Digital Image Computing: Techniques and Applications. In: DICTA 2016: International Conference on Digital Image Computing: Techniques and Applications, 30 November - 2 December 2016, Gold Coast, QLD, Australia
Suwanwiwat H, Blumenstein M and Pal U (2015) A complete automatic short answer assessment system with student identification. Proceedings of the 13th International Conference on Document Analysis and Recognition. In: ICDAR 2015: 13th International Conference on Document Analysis and Recognition, 23-26 August 2015, Nancy, France
Suwanwiwat H, Blumenstein M and Pal U (2015) Short answer question examination using an automatic off-line handwriting recognition system and a novel combined feature. Proceedings of the International Joint Conference on Neural Networks. In: IJCNN 2015: International Joint Conference on Neural Networks, 12-17 July 2015, Killarney, Ireland

More: ResearchOnline@JCU stores 16+ research outputs authored by Dr Art (Hemmaphan) Suwanwiwat from 2013 onwards.

Current Funding

Current and recent Research Funding to JCU is shown by funding source and project.

Australian Council of Deans of ICT (ACDICT) Learning & Teaching Academy (ALTA) - Learning & Teaching Grant Scheme

Sustainably enhancing social presence while balancing teacher and student wellbeing

Indicative Funding: $11,591 over 1 year
Summary: As Australia moves to a post-Covid normal, online blended learning approaches in tertiary education have become more prevalent. Studies have shown that developing social presence for students and staff can lead to increased wellbeing. However, the steps to ensuring social presence are not well understood or studied in the Information Systems discipline. This project will investigate both student and staff perspectives in supporting wellbeing through social presence and highlight best practices at two Australian universities (JCU and QUT) and in the wider community. Outputs will be best practice guidelines and academic papers highlighting these learnings.
Investigators: Dianna Hardy, Jason Holdsworth, Art (Hemmaphan) Suwanwiwat, Trina Myers, Jason Watson, Sharon Altena and Wasana Bandara (Indigenous Education & Research Centre, College of Science & Engineering and Queensland University of Technology)
Keywords: Social Presence; Student Wellbeing; Educator Wellbeing; Online Teaching; scalability; Blended Learning

Fisheries Research & Development Corporation - Annual Competitive Round

Application of a machine learning approach for effective stock management of abalone

Indicative Funding: $115,649 over 2 years
Summary: Determining the number and size distribution of abalone present at various stages of production is critical information for effective stock management. Currently the Australian abalone aquaculture industry spends in the order of $25,000 per annum, per farm, gathering this information by hand. However, the resulting data is of mediocre quality, is limited in its scope, and collecting the data causes stress to the animals which can compromise growth and survival. Automated counting and measuring of abalone will increase farm efficiency and productivity in the short term and, in the longer term, will provide an advanced platform for further R&D improvements. Artificial intelligence and machine learning has now matured to a point that accurately counting and measuring abalone is possible using this approach. This project would involve the development, training and validation of a machine learning model to identify, segment and measure quantitative abalone traits in production systems, and render the product data to be accessible and applicable for farmers.
Investigators: Jan Strugnell, Marcus Sheaves, Carlo Mattone, Ickjai Lee, Joanne Lee, Jason Holdsworth and Art (Hemmaphan) Suwanwiwat (College of Science & Engineering)
Keywords: Abalone (Haliotidae); Machine Learning

World Wide Fund for Nature (US) - Contract Research

From Coastal Communities to Cloud Communities ? New Application and Artificial Intelligence to Monitor Fish Stocks Using Photos ? Application Development

Indicative Funding: $53,100 over 1 year
Summary: The Project aims at develop an artificial intelligence capable to autonomously identify fish species and number from images collected at fish markets in remote location, so that effective catch rate can be evaluated and management policies can be developed.
Investigators: Marcus Sheaves, Carlo Mattone, Michael Bradley, Joanne Lee, Jason Holdsworth, Art (Hemmaphan) Suwanwiwat and Ickjai Lee (College of Science & Engineering)
Keywords: Artificial Intelligence; Phone App; Caught Fish; Catch Rate

Supervision

Advisory Accreditation: I can be on your Advisory Panel as a Primary or Secondary Advisor.

These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.

Current

Investigating Security Vulnerabilities in Healthcare IoT (PhD , Secondary Advisor)

Completed

A data-driven approach towards a realistic and generic crowd simulation framework (2020, PhD , Secondary Advisor)

Collaboration

The map shows research collaborations by institution from the past 7 years.
Note: Map points are indicative of the countries or states that institutions are associated with.