Graduate Students

Ph.D. Students

• Zagon Bussabong – Automated Image Captioning for Visually Impaired with Deep Learning Techniques (การสร้างคำบรรยายภาพอัตโนมัติสำหรับผู้บกพร่องทางสายตาด้วยเทคนิคการเรียนรู้เชิงลึก)
  • Bussabong, Z., Jarutan, P., Okafor, E., & Surinta, O. (2025). Enhancing Image Caption Performance with Improved Visual Attention Mechanism. ICIC Express Letters, Part B: Applications, 16(1), Accepted.
• Praetawan Jarutan – Text Recognition in Images using Deep Convolutional Recurrent Neural Network and Language Models (การรู้จำข้อความในรูปภาพโดยใช้โครงข่ายประสาทเทียมคอนโวลูชันแบบวนกลับและแบบจำลองทางภาษา)
  • Jarutan, P., Hanyong, T., Bussabong, Z., Okafor, E., & Surinta, O. (2025). Multimodal Fusion of Convolutional Recurrent Neural Network and Language Models for Text Recognition. ICIC Express Letters, Part B: Applications, 16(1), Accepted.
• Teerasak Sungsri – Deep Learning Techniques for Hybrid Multimodal Emotion Recognition (วิธีการเรียนรู้เชิงลึกสำหรับการรู้จำอารมณ์แบบผสมผสาน)
  • Sungsri, T., Sungsri, T., Okafor, E., & Surinta, O. (2025). Multimodal Emotion Recognition Based on Hybrid Ensemble Deep Learning Framework. ICIC Express Letters, Part B: Applications, 16(2), Accepted.
• Teerapong Sungsri – Dynamic Thai Sign Language Recognition using Deep Learning with Convolutional Neural Network and Transformer Techniques (การรู้จำภาษามือไทยแบบไดนามิกโดยใช้การเรียนรู้เชิงลึกด้วยเทคนิคโครงข่ายประสาทเทียมแบบคอนโวลูชันและทรานส์ฟอร์มเมอร์)
  • Sungsri, T., Sungsri, T., Okafor, E., & Surinta, O. (2025). Fusion-Based Convolutional Recurrent Neural Network for Improved Dynamic Thai Fingerspelling Recognition. ICIC Express Letters, Part B: Applications, 16(2), Accepted.
• Pichit Wandee – Plant Leaf Disease Classification Based on Deep Learning with Ensemble Methods (การรู้จำโรคใบพืชบนพื้นฐานการเรียนรู้เชิงลึกด้วยกระบวนการเอนเซมเบิล)
• Wimolsree Getsophon – Deep Learning for Video Understanding
  • Getsopon, W. and Surinta, O. (2022). Fusion Lightweight Convolutional Neural Networks and Sequence Learning Architectures for Violence Classification. ICIC Express Letters, Part B: Applications, 13(10), 1027-1035. doi: 10.24507/icicelb.13.10.1027. (Scopus Q3)
• Narong Boonsirisumpun – Automatic Vehicle Detection and Classification System using Advanced Deep Learning Architectures
  • Boonsirisumpun, N., Okafor, E., and Surinta, O. (2024). Vehicle image datasets for image classification. Data in Brief, 53, 110133. https://doi.org/10.1016/j.dib.2024.110133
  • Boonsirisumpun, N. (2023). Automatic Vehicle Detection and Classification System using Advanced Deep Learning Architectures (PhD Dissertation, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand).
  • Boonsirisumpun, N. and Surinta, O. (2022). Ensemble Multiple CNNs methods with partial Training Set for Vehicle Image Classification. Science, Engineering and Health Studies, accepted (Scopus Q3)
  • Boonsirisumpun, N. and Surinta, O. (2022). Fast and Accurate Deep Learning Architecture on Vehicle Type Recognition. Current Applied Science and Technology, 22(1) (January-February 2022), 1-16. (Scopus Q4)
• Prem Enkvetchakul – Deep Convolutional Neural Network to Recognize Plant Leaf Images
  • Enkvetchakul, P. (2022). Deep Convolutional Neural Network to Recognize Plant Leaf Images (PhD Dissertation, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand).
  • Enkvetchakul, P. and Surinta, O. (2022). Stacking Ensemble of Lightweight Convolutional Neural Networks for Plant Leaf Disease Recognition. ICIC Express Letters, 16(5), 521-528. doi: 10.24507/icicel.16.05.521. (Scopus Q3)
  • Enkvetchakul, P. and Surinta, O. (2022). Effective Data Augmentation and Training Techniques for Improving Deep Learning in Plant Leaf Disease Recognition. Applied Science and Engineering Progress, 15(3), 3810. https://doi.org/10.14416/j.asep.2021.01.003. (Scopus Q2)
• Sarayut Gonwirat – Deep Learning in Historical Document Image Analysis and Recognition
  • Gonwirat, S. (2022). Historical Document Transcription using Deep Learning (PhD Dissertation, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand).
  • Gonwirat, S. and Surinta, O. (2022). DeblurGAN-CNN: Effective Image Denoising and Recognition for Noisy Handwritten Characters. IEEE Access, 10, 90133-90148. doi: 10.1109/ACCESS.2022.3201560. (ISI Q2, Impact factor 3.367)
  • Gonwirat, S. and Surinta, O. (2022). CycleAugment: Efficient Data Augmentation Strategy for Handwritten Text Recognition in Historical Document Images. Engineering and Applied Science Research, 49(4), 505-520. https://ph01.tci-thaijo.org/index.php/easr/article/view/246869 (Scopus Q3)
  • Gonwirat, S. and Surinta, O. (2020). Improving Recognition of Thai Handwritten Characters with Deep Convolutional Neural Networks, in Information Science and System (ICISS), The 3rd International Conference on, 82-87. slide, video, https://doi.org/10.1145/3388176.3388181
• Siriwiwat Lata – The Automated Sign Language Translation System using Deep Learning
  • Lata, S. (2023). The Automated Sign Language Translation System Using Deep Learning (PhD Dissertation, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand).
  • Lata, S., Phiphitphatphaisit, S., Gonwirat, S. and Surinta, O.(2022). Dynamic Fingerspelling Recognition from Video Using Deep Learning Approach: From Detection to Recognition. ICIC Express Letters, Part B: Applications, 13(9), 949-957. doi: 10.24507/icicelb.13.09.949. (Scopus Q3)
  • Lata, S. and Surinta, O. (2022). An End-to-End Thai Fingerspelling Recognition Framework with Deep Convolutional Neural Networks. ICIC Express Letters, 16(5), 529-536. doi: 10.24507/icicel.16.05.529. (Scopus Q3)
• Thipwimon Chompookham – The Automated Plant Leaf Image Classification System using Deep Learning
  • Choompookham, T., Phiphitphatphaisit, S., Okafor, E., & Surinta, O. (2024). Robust Model Selection for Plant Leaf Image Recognition Based on Evolutionary Ant Colony Optimization with Learning Rate Schedule, IEEE Access. (Accepted). (ISI Q2, Impact Factor 3.4: Scopus Q1, CiteScore 9.0, Percentile 92%)
  • Choompookham, T., Okafor, E., and Surinta, O. (2024). Mulberry leaf dataset for image classification task. Data in Brief, 54, 110281. https://doi.org/10.1016/j.dib.2024.110281 (Scopus Q1, CiteScore 3.1, Percentile 76%)
  • Chompookham, T. (2022). The Automated Plant Leaf Image Classification System using Deep Learning (PhD Dissertation, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand).
  • T. Chompookham and O. Surinta (2021). Ensemble Methods with Deep Convolutional Neural Networks for Plant Leaf Recognition. ICIC Express Letters, 15(6), 553-565. (Scopus Q3)
  • T. Chompookham, S. Gonwirat, S. Lata, S. Phiphitphatphaisit and O. Surinta (2020). Plant Leaf Image Recognition using Multiple-grid Based Local Descriptor and Dimensionality Reduction Approach, in Information Science and System (ICISS), The 3rd International Conference on, 72-77. slide, video, https://doi.org/10.1145/3388176.3388180
• Sangdaow Noppitak – Deep Learning for Land Use and Land Cover in Aerial Images
  • Noppitak, S. (2022). Deep Learning for Land Use and Land Cover in Aerial Images (PhD Dissertation, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand).
  • Noppitak, S. and Surinta, O. (2022). dropCyclic: Snapshot Ensemble Convolutional Neural Network Based on a New Learning Rate Schedule for Land Use Classification. IEEE Access, 10, 60725-60737. doi: 10.1109/ACCESS.2022.3180844. (ISI Q2, Impact factor 3.367)
  • S. Noppitak and O. Surinta (2021). Ensemble Convolutional Network Architectures for Land Use Classification in Economic Crops Aerial Images. ICIC Express Letters, 15(6), 531-543. (Scopus Q3)
  • S. Noppitak, S. Gonwirat, and O. Surinta (2020). Instance Segmentation of Water Body from Aerial Image using Mask Region-based Convolutional Neural Network, in Information Science and System (ICISS), The 3rd International Conference on, 61-66. slide, video, https://doi.org/10.1145/3388176.3388184
• Sirawan Phiphitphatphaisit – Deep Learning Approach for Food Image Recognition System. (Thesis)
  • Phiphitphatphaisit, S., and Surinta, O. (2024). Multi-Layer Adaptive Spatial-Temporal Feature Fusion Network for Efficient Food Image Recognition. Expert Systems with Applications, 255, Part D, Article 124834. doi: 10.1016/j.eswa.2024.124834
  • Phiphiphatphaisit, S. (2022). Deep Learning Approach for Food Image Recognition System (PhD Dissertation, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand).
  • Phiphitphatphaisit, S. and Surinta, O. (2021). Deep Feature Extraction Technique Based on Conv1D and LSTM Network for Food Image Recognition. Engineering and Applied Science Research, 48(5), 581-592. (Scopus Q4)
  • Phiphitphatphaisit, S. and Surinta, O. (2020). Food Image Classification with Improved MobileNet Architecture and Data Augmentation, in Information Science and System (ICISS), The 3rd International Conference on, 51-56. slide, video, https://doi.org/10.1145/3388176.3388179

Master Students

• Pichada Saichua, Classification of Diabetic Retinopathy Images using Deep Learning
  • Saichua, P. (2022). Classification of Diabetic Retinopathy Images using Deep Learning (Master Thesis, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand)
  • Saichua, P. and Surinta, O. (2022). Comparative Study between Ensemble and Fusion Convolutional Neural Networks for Diabetic Retinopathy Classification. ICIC Express Letters, 16(4), 401-408. (Scopus Q3)
• Thanadol Singkhornart, 2021, Deep Learning for Video Subtitle Detection and Recognition, (Thesis)
  • Singkhornart, T. (2022). Deep Learning for Video Subtitle Detection and Recognition (Master Thesis, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand)
  • Singkhornart, T. and Surinta, O. (2022). Multi-Language Video Subtitle Recognition with Convolutional Neural Network and Long Short-Term Memory Networks. ICIC Express Letters, 16(6), 647-655. doi: 10.24507/icicel.16.06.647. (Scopus Q3)
• Phukkaraphon Ardarsa, 2021, The Analysis of Water Quality using Clustering Techniques, (Thesis)
  • Ardarsa, P. (2021). The Analysis of Water Quality using Clustering Techniques (Master Thesis, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand)
  • Ardarsa, P. and Surinta, O. (2021). Water Quality Assessment in the Lam Pa Thao Dam, Chaiyaphum, Thailand with K-Means Clustering Algorithm, in Research, Invention and Innovation Congress (RI2C), 35-39.
• Kuannabha Pimcharee, 2021, Data Mining Approaches for Loan Decision of a Bank, (Thesis)
  • Pimcharee, K. (2021). Data Mining Approaches for Loan Decision of a Bank (Master Thesis, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand)
  • Pimcharee, K. and Surinta, O. (2021). Data Mining Approaches in Personal Loan Approval. Engineering Access, 8(1), 15-21. (TCI2)
• Jakkarin Sanuksan, 2019, Applying of Deep Learning Techniques for Plant Image Recognition in a Natural Environment, (Thesis, Cover, Slide, PNE Dataset)
  • Sanuksan, J. (2019). Applying of Deep Learning Techniques for Plant Image Recognition in a Natural Environment (Master Thesis, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand)
  • Sanuksan, J. and Surinta, O. (2019). Deep Convolutional Neural Networks for Plant Recognition in Natural Environment. Journal of Science and Technology Mahasarakham University, 38(2), 113-124. (TCI 1)
• Tanaphon Roempluk, 2019, A Machine Learning Approach for Detecting Distributed Denial of Service Attacks, (Thesis, Slide)
  • Roempluk, T. (2019). A Machine Learning Approach for Detecting Distributed Denial of Service Attacks (Master Thesis, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand)
  • Roempluk, T. and Surinta, O. (2019). A Machine Learning Approach for Detecting Distributed Denial of Service Attacks. in Digital Arts, Media and Technology (ICDAMT), The 4th International Conference on, 146-149.
• Nattawat Ruksaard, 2018, Methods of Silk Pattern Image Retrieval with Small Sample Sizes, (Thesis, Cover, Dataset)
  • Ruksaard, N. (2018). Methods of Silk Pattern Image Retrieval with Small Sample Sizes (Master Thesis, Department of Information Technology, Faculty of Informatics, Mahasarakham University, Mahasarakham, Thailand)
  • Raksaard, N. and Surinta, O. (2018). Comparative Study Between Local Descriptors and Deep Learning for Silk Pattern Image Retrieval. Journal of Science and Technology Mahasarakham University, 37(6), 736-746.