Publications

Article

• [J48] Phiphitphatphaisit, S., & 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. https://doi.org10.1016/j.eswa.2024.124834 (ISI Q1, Impact Factor 7.5: Scopus Q1, CiteScore 13.8, Percentile 96%)
  
• [J47] 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, 12, 132369-132389. https://doi.org/10.1109/ACCESS.2024.3457753 (ISI Q2, Impact Factor 3.4: Scopus Q1, CiteScore 9.0, Percentile 92%)
• [J46] Sangkatip, W., Chomphuwiset, P., Bunluewong, K., Mekruksavanich, S., Okafor, E., & Surinta, O. (2024). Improving Neural Network-Based Multi-Label Classification with Pattern Loss Penalties. IEEE Access, 12, 52237 – 52248. https://doi.org/10.1109/ACCESS.2024.3386841 (ISI Q2, Impact Factor 3.4: Scopus Q1, CiteScore 9.0, Percentile 92%)
• [J45] Rojarath, A., Songpan, W., & Surinta, O. (2025). Depression Classification with Imbalanced Data Problems: Literature Survey, Engineering Access, 11(2), 2025. (Accepted)
• [J44] Rojarath, A., Songpan, W., Okafor, E., & Surinta, O. (2025). Enhancing Personality Characteristics Analysis with SMOTE and Association Rule Mining: A Case Study on Introverts and Extroverts, ICIC Express Letters, 19(6). (Accepted)
• [J43] Rabruen, A., Pokkate, P., Surinta, O., and Khruahong, A. (2025). Sentiment Analysis of Thai Laborers’ Perceptions of Working Abroad: A Machine Learning Approach using Youtube Comments, ICIC Express Letters, Part B: Applications, 16(3), 333-341. doi: 10.24507/icicelb.16.03.333 https://doi.org/10.24507/icicelb.16.03.333
• [J42] Boonchoo, C., Supansomboon, S., Pramote, O.-U., Surinta, O., & Khruahong, S. (2025). Prediction of Stone Types using Convolutional Neural Networks Technique, ICIC Express Letters, Part B: Applications, 16(3), 343-350. doi: 10.24507/icicelb.16.03.343
• [J41] Mekruksavanich, S., Surinta, O. & Jitpattanakul, A. (2025). A deep neural network with aggregated residual transformation for smartwatch-based human activity recognition in real world situations. ICIC Express Letters, 19(3), 343-351. doi: 10.24507/icicel.19.03.343
• [J40] 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), 201-210. doi: 10.24507/icicelb.16.02.201
• [J39] 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), 73-82. doi: 10.24507/icicelb.16.01.73
• [J38] 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), 83-91. doi: 10.24507/icicelb.16.01.83
• [J37] 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(1), 93-102. doi: 10.24507/icicelb.16.01.93
• [J36] Mekruksavanich, S., Surinta, O. & Jitpattanakul, A. (2024). sEMG-based muscular movement recognition for hand prothesis using deep learning approaches. ICIC Express Letters, Part B: Applications, 15(12), 1311-1318. doi: 10.24507/icicelb.15.12.1311. (Scopus Q4)
• [J35] Rojarath, A., Jantama, T., Srirat, W., Mookpakdee, N., khumwiso, K., & Surinta, O. (2024). Factors analysis affecting stroke disease using association rules. Journal of Science and Technology Mahasakham University, 43(3), 206-222. (TCI 1) [In Thai]
• [J34] Choompookham, T., Okafor, E., & 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%)
• [J33] Boonsirisumpun, N., Okafor, E., & Surinta, O. (2024). Vehicle image datasets for image classification. Data in Brief, 53, 110133. https://doi.org/10.1016/j.dib.2024.110133 (Scopus Q1, CiteScore 3.1, Percentile 76%)
• [J32] Mekruksavanich, S., Jantawong, P., Surinta, O., & Jitpattanakul, A. (2024). Road surface classification for intelligent vehicle perception based on inertial sensors. ICIC Express Letters, 18(1), 79-86. doi: 10.24507/icicel.18.01.79 (Scopus Q3)
• [J31] Jantawong, P., Surinta, O., Jitpattanakul, A., & Mekruksavanich, S. (2024). Recognition of exercise activity using CNN and LSTM based on accelerometer data. ICIC Express Letters, 18(1), 69-77. doi: 10.24507/icicel.18.01.69 (Scopus Q3)
• [J30] Mekruksavanich, S., Jantawong, P., Surinta, O., Hnoohom, N., & Jitpattanakul, A. (2023). Deep learning for recognizing daily human activities using smart home sensors. ICIC Express Letters, 17(12), 1375-1383. doi: 10.24507/icicel.17.12.1375 (Scopus Q3)
• [J29] Gonwirat, S., Surinta, O., & Pawara. P. (2022). Fusion convolutional recurrent neural networks for Thai and English video subtitle recognition, ICIC Express Letters, 16(12), 1331-1339. doi: 10.24507/icicel.16.12.1331 (Scopus Q3)
• [J28] Boonsirisumpun, N., & Surinta, O. (2022). Ensemble multiple CNNs methods with partial training set for vehicle image classification. Science, Engineering and Health Studies, 16, 22020001. doi: 10.14456/sehs.2022.12 (Scopus Q3)
• [J27] Gonwirat, S., & 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)
• [J26] Noppitak, S., & 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)
• [J25] Getsopon, W., & 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)
  
• [J24] Lata, S., Phiphitphatphaisit, S., Gonwirat, S., & 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)
• [J23] Enkvetchakul, P., Surinta, O., & Noppitak, S. (2022). Effective data resampling and meta-learning convolutional neural networks for diabetic retinopathy recognition. ICIC Express Letters, Part B: Applications, 13(9), 939-948. doi: 10.24507/icicelb.13.09.939. (Scopus Q3)
• [J22] Gonwirat, S., & 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. (Scopus Q3)
• [J21] Enkvetchakul, P., & 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)
• [J20] Singkhornart, T., & 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)
• [J19] Lata, S., & 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)
• [J18] Enkvetchakul, P., & 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)
• [J17] Saichua, P., & Surinta, O. (2022). Comparative study between ensemble and fusion convolutional neural networks for diabetic retinopathy classification. ICIC Express Letters, 16(4), 401-408. doi: 10.24507/icicel.16.04.401. (Scopus Q3)
• [J16] Pimcharee, K., & Surinta, O. (2022). Data mining approaches in personal loan approval. Engineering Access, 8(1), 15-21. (Scopus, TCI 2)
• [J15] Boonsirisumpun, N., & 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)
• [J14] Bunluewong, K., & Surinta, O. (2021). Semi-automated mushroom cultivation house using internet of things. Engineering Accees, 7(2), 181-188. (Scopus, TCI 2)
• [J13] Gonwirat, S., & Surinta, O. (2021). Optimal weighted parameters of ensemble CNNs based on a differential evolution algorithm for enhancing pornographic image classification. Engineering and Applied Science Research, 48(5), 560-569. (Scopus Q4)
• [J12] Phiphitphatphaisit, S., & 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)
• [J11] Puangsuwan, T., & Surinta, O. (2021). Enhancement of plant disease classification based on snapshot ensemble convolutional neural network. ICIC Express Letters, 15(6), 669-680. (Scopus Q3)
• [J10] Chompookham, T., & Surinta, O. (2021). Ensemble methods with deep convolutional neural networks for plant leaf recognition. ICIC Express Letters, 15(6), 553-565. (Scopus Q3)
• [J9] Noppitak, S., & Surinta, O. (2021). Ensemble convolutional network architectures for land use classification in economic crops aerial images. ICIC Express Letters, 15(6), 531-543. (Scopus Q3)
• [J8] Tantrabundit, P., Wongsim, M., & Surinta, O. (2020). Technology acceptance model: The evidence of NodeMCU’s mushroom house control system in Thailand. Journal of Accountancy and Management, 12(1), 42-54. (TCI 2)
• [J7] Sanuksan, J., & 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) [In Thai]
• [J6] Raksaard, N., & 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. (TCI 1) [In Thai]
• [J5] Surinta, O. (2018). Local descriptors approach for pornographic image classification. Journal of Science and Technology Mahasarakham University, 37(3), 439-448. (TCI 1) [In Thai]
• [J4] Surinta, O., & Bunluewong, K. (2017). Handwritten character recognition using k-nearest neighbors classifier – A survey. Journal of Science and Technology Mahasarakham University, 36(1), 117-129. (TCI 1)
• [J3] Surinta, O., Karaaba, M.F., Schomaker, L.R.B., & Wiering, M.A. (2015). Recognition of handwritten characters using local gradient feature descriptors. Engineering Applications of Artificial Intelligence, (45), 405-414. (SJR Q1, 0.87; IF 2.819)
• [J2] Codreanu, V., Dröge, B., Williams, D., Yasar, B., Yang, P., Liu, B., Dong, F., Surinta, O., Schomaker, L.R.B, Roerdink, J.B.T.M., & Wiering, M.A. (2014). Evaluating automatically parallelized versions of the Support Vector Machine. Concurrency and Computation: Practice and Experience, 1-21. (SJR Q2, 0.28; IF 1.114)
• [J1] Surinta, O., & Nitsuwat, S. (2005). Handwritten Thai character recognition using Fourier descriptors and robust C-prototype. Information Technology Journal, 92-96.

Proceeding

• [C31] Khruahong, S., Surinta, O., Lam, S.C. (2022). Sentiment Analysis of Local Tourism in Thailand from YouTube Comments Using BiLSTM. In: Surinta, O., Kam Fung Yuen, K. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2022. Lecture Notes in Computer Science(), vol 13651. Springer, Cham. https://doi.org/10.1007/978-3-031-20992-5_15
• [C30] 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. doi: https://doi.org/10.1109/RI2C51727.2021.9559811
• [C29] Khamket, T. and Surinta, O.(2021). Feature Extraction Efficient for Face Verification Based on Residual Network Architecture. in Multi-disciplinary Trends in Artificial Intelligence (MIWAI), The 14th International Conference on, 71-80. doi: https://doi.org/10.1007/978-3-030-80253-0_7, slide
• [C28] Khamket, T. and Surinta, O. (2020). Comparative Study Between Texture Feature and Local Feature Descriptors for Silk Fabric Pattern Image Recognition. in Information Science and System (ICISS), The 3rd International Conference on, 93-98. slide, video, doi: https://doi.org/10.1145/3388176.3388201
• [C27] 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, doi: https://doi.org/10.1145/3388176.3388181
• [C26] Noppitak, S., Gonwirat, S., and Surinta, O. (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, doi: https://doi.org/10.1145/3388176.3388184
• [C25] Chompookham, T., Gonwirat, S., Lata, S., Phiphitphatphaisit, S. and Surinta, O. (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, doi: https://doi.org/10.1145/3388176.3388180
• [C24] 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, doi: https://doi.org/10.1145/3388176.3388179
• [C23] Khunthi, S., Saichua, P. and Surinta, O. (2019). Effective Face Verification Systems based on Histogram of Oriented Gradients and Deep Learning Techniques. in Artificial Intelligence and Natural Language Processing (iSAI-NLP), The 14th International Joint Symposium on, 215-219.  slide, doi: https://doi.org/10.1109/iSAI-NLP48611.2019.9045237
• [C22] Surinta, O. and Khamket, T. (2019). Gender Recognition from Facial Images using Local Gradient Feature Descriptors. in Artificial Intelligence and Natural Language Processing (iSAI-NLP), The 14th International Joint Symposium on, 346-351.  slide, doi: https://doi.org/10.1109/iSAI-NLP48611.2019.9045689
• [C21] Khruahong, S. and Surinta, O. (2019). Develop the Framework Conception for Hybrid Indoor Navigation for Monitoring Inside Building using Quadcopter. in Artificial Intelligence and Natural Language Processing (iSAI-NLP), The 14th International Joint Symposium on, 352-357.  slide, pdf, doi: https://doi.org/10.1109/iSAI-NLP48611.2019.9045445
• [C20] Surinta, O. and Khamket, T. (2019). Recognizing Pornographic Images using Deep Convolutional Neural Networks. in Digital Arts, Media and Technology (ICDAMT), The 4th International Conference on, 150-154.  slide, doi: https://doi.org/10.1109/ECTI-NCON.2019.8692296
• [C19] 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.  slide, doi: http://doi.org/10.1109/ECTI-NCON.2019.8692243
• [C18] Surinta, O. and Khruahong, S. (2019). Tracking People and Objects with an Autonomous Unmanned Aerial Vehicle using Face and Color Detection. in Digital Arts, Media and Technology (ICDAMT), The 4th International Conference on, 206-120.  slide, doi: http://doi.org/10.1109/ECTI-NCON.2019.8692269
• [C17] Wongsim, M., Sonthiprasat, R. and Surinta, O. (2018). Factors Influencing the Adoption of Agricultural Management Information Systems in Thailand. in The 3rd Technology Innovation Management and Engineering Science International Conference (TIMES-iCON), 1-4. doi: http://doi.org/10.1109/TIMES-iCON.2018.8621831
• [C16] Pawara, P., Okafor, E., Surinta, O., Schomaker, L.R.B. and Wiering, M.A. (2017). Comparing Local Descriptors and Bags of Visual Words to Deep Convolutional Neural Networks for Plant Recognition, in Pattern Recognition Applications and Methods (ICPRAM), The 6th International Conference on, 479-486.
• [C15] Okafor, E., Pawara, P., Karaaba, F., Surinta, O., Codreanu, V., Schomaker, L.R.B. and Wiering, M.A. (2016). Comparative Study Between Deep Learning and Bag of Visual Words for Wild-Animal Recognition, in Computational Intelligence (SSCI), IEEE Symposium Series on, 1-8.
• [C14] Karaaba, F., Surinta, O., Schomaker, L.R.B. and Wiering, M.A. (2016). Robust Face Identification with Small Sample Sizes using Bag of Words and Histogram of Oriented Gradients, in Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAAP), The 10th International Joint Conference on, 582-589.
• [C13] Karaaba, F., Surinta, O., Schomaker, L.R.B., and Wiering, M.A. (2015). Robust Face Recognition by Computing Distances From Multiple Histograms of Oriented Gradients, in Computational Intelligence in Biometrics and Identity Management (IEEE CIBIM), IEEE Symposium Series on, 2015, 203-209.
• [C12] Surinta, O., Karaaba, M.F., Mishra, T.K., Schomaker, L.R.B., and Wiering, M.A. (2015). Recognizing Handwritten Characters with Local Descriptors and Bags of Visual Words, in Engineering Applications of Neural Networks (EANN), The 16th International Conference on, 255-264. slide
• [C11] Karaaba, F., Surinta, O., Schomaker, L.R.B., and Wiering, M.A. (2015). In-Plane Rotational Alignment of Faces by Eye and Eye-Pair Detection, in Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAAP), The 10th International Joint Conference on, 392-399. poster
• [C10] Surinta, O., Holtkamp, M., Karaaba, M.F., van Oosten, JP., Schomaker, L.R.B., and Wiering, M.A. (2014). A* Path Planning for Line Segmentation of Handwritten Documents, in Frontiers in Handwriting Recognition (ICFHR), The 14th International Conference on, 175-180. poster
• [C9] Surinta, O., Schomaker, L.R.B., and Wiering, M.A. (2013) A comparison of feature and pixel-based methods for recognizing handwritten Bangla digits, in Document Analysis and Recognition (ICDAR), The 12 International Conference on, 165-169. poster
• [C8]Surinta, O., Schomaker, L.R.B. and Wiering, M.A. (2012). Handwritten Character Classification Using the Hotspot Feature Extraction Technique, in Pattern Recognition Applications and Methods (ICPRAM), The 1st International Conference on, 261-264. poster
• [C7] Surinta, O. (2009). Optimization of Line Segmentation Techniques for Thai Handwritten Documents, in Natural Language Processing (SNLP), The 8th International Symposium on, 180-183.
• [C6] Surinta, O. and Chamchong, R. (2008). Image Segmentation of Historical Handwriting from Palm Leaf Manuscripts, in Intelligent Information Processing, (288), 182-189.
• [C5] Leesom, N. and Surinta, O. (2007). Thai Handwritten Character Segmentation from Digital Image Documents, the 3rd Mahasarakham University Research Conference, 123-132.
• [C4] Surinta, O. (2007). Patient Record System, in Computing and Information Technology (NCCIT), The 3rd National Conference on, 1-6.
• [C3] Chamchong, R., Surinta, O., Udom, T., and Thongchan, P. (2007). Text Line Segmentation from Palm Leaf Manuscripts, in Computing and Information Technology (NCCIT), The 3rd National Conference on, 1-6.
• [C2] Surinta, O. and Jareanpon, C. (2006). Comparison of Image Analysis for Thai Handwritten Character Recognition, in Intelligent Information Processing, (228), 373-382.
• [C1] Jareanpon, C. and Surinta, O. (2006). Handwritten Recognition with Neural Network, in Advanced Image Technology (IWAIT), The International Workshop on, 1-6.