4611. Machine learning
| Title | 4611. Machine learning |
|---|---|
| Parent | 46. Information and Computing Sciences |
Latest research outputs
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eXplainable expert systems for potato tuber yield prediction in the Maritime provinces of Canada
Jamei, M., Farooque, A., Ali, M., Karbasi, M., Afzaal, H., Cheema, S.J., Zaman, Q.U., Woon, K.S. and Sheridan, P.. 2025. "eXplainable expert systems for potato tuber yield prediction in the Maritime provinces of Canada." Computers and Electronics in Agriculture. 238. https://doi.org/https://doi.org/10.1016/j.compag.2025.110831Article
Deep learning techniques for automated coronary artery segmentation and coronary artery disease detection: A systematic review of the last decade (2013-2024)
Yaman, Suleyman, Aslan, Ozkan, Güler, Hasan, Sengur, Abdulkadir, Hafeez-Baig, Abdul, Tan, Ru-San, Deo, Ravinesh C, Barua, Prabal Datta and Acharya, U. Rajendra. 2025. "Deep learning techniques for automated coronary artery segmentation and coronary artery disease detection: A systematic review of the last decade (2013-2024)." Computer Methods and Programs in Biomedicine. 268. https://doi.org/doi:10.1016/j.cmpb.2025.108858Article
Multi-step ahead significant wave height forecasting using global and local view graph representation based on GRU model
Diykh, Mohammed, Ali, Mumtaz, Jamei, Mehdi, Prasad, Ramendra, Labban, Abdulhaleem H., Abdulla, Shahab, Singh, Niharika and Farooque, Aitazaz Ahsan. 2025. "Multi-step ahead significant wave height forecasting using global and local view graph representation based on GRU model." Ocean Engineering. 340 (Part 2). https://doi.org/10.1016/j.oceaneng.2025.122314Article
Uncertainty assessment based on data decomposition and Boruta-driven extreme gradient boosting to predict spatiotemporal urban air dust heavy metal index
Seifi, Akram, Soltani-Gerdefaramarzi, Somayeh and Ali, Mumtaz. 2025. "Uncertainty assessment based on data decomposition and Boruta-driven extreme gradient boosting to predict spatiotemporal urban air dust heavy metal index." Atmospheric Pollution Research. 16 (11). https://doi.org/10.1016/j.apr.2025.102654Article
Designing advanced feature selection and uncertainty quantification-based deep learning approach to predict chlorophyll-a and water bloom risks in dam reservoir
Seifi, Akram, Madvar, Hossien Riahi, Davarpanah, Rouhollah, Ali, Mumtaz and Mashat, Abdul-Wahab. 2025. "Designing advanced feature selection and uncertainty quantification-based deep learning approach to predict chlorophyll-a and water bloom risks in dam reservoir." Journal of Water Process Engineering. 77. https://doi.org/10.1016/j.jwpe.2025.108341Article
AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts
Shaik, Thanveer, Tao, Xiaohui, Li, Lin, Xie, Haoran, Dai, Hong-Ning, Zhao, Feng and Yong, Jianming. 2025. "AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts." Brain Informatics. 12 (1). https://doi.org/10.1186/s40708-025-00262-1Article
Causal integration in graph neural networks toward enhanced classification: benchmarking and advancements for robust performance
Job, Simi, Tao, Xiaohui, Cai, Taotao, Li, Lin, Sheng, Quan Z, Xie, Haoran and Yong, Jianming. 2025. "Causal integration in graph neural networks toward enhanced classification: benchmarking and advancements for robust performance." World Wide Web. 28 (3). https://doi.org/10.1007/s11280-025-01343-1Article
Modeling the Effect of Prior Knowledge on Memory Efficiency for the Study of Transfer of Learning: A Spiking Neural Network Approach
Fard, Mojgan Hafezi, Petrova, Krassie, Kasabov, Nikola Kirilov and Wang, Grace Y.. 2025. "Modeling the Effect of Prior Knowledge on Memory Efficiency for the Study of Transfer of Learning: A Spiking Neural Network Approach." Big Data and Cognitive Computing. 9 (7). https://doi.org/10.3390/bdcc9070173Article
Leveraging Advanced Data-Driven Approaches to Forecast Daily Floods Based on Rainfall for Proactive Prevention Strategies in Saudi Arabia
Aldhafiri, Anwar Ali, Ali, Mumtaz and Labban, Abdulhaleem H.. 2025. "Leveraging Advanced Data-Driven Approaches to Forecast Daily Floods Based on Rainfall for Proactive Prevention Strategies in Saudi Arabia." Water. 17 (11). https://doi.org/10.3390/w17111699Article
An Enhanced Data Collection System for Social Enterprises: Securing Impact with Machine Learning and Cryptography
Muttaki, Fardin, Sahi, Aqeel, Abdulla, Shahab and Aljebur, Kaled. 2025. "An Enhanced Data Collection System for Social Enterprises: Securing Impact with Machine Learning and Cryptography ." FinTech and Sustainable Innovation (FSI). https://doi.org/10.47852/bonviewFSI52025209Article
Predicting near-real-time total water level with an artificial intelligence model based on Australia's tidal wave energy belt dataset
AL-Musaylh, Mohanad S., Gharineiat, Zahra, Al‑Dafaie, Kadhem, Jasim, Khalid Fadhil, Sharma, Ekta and Nahi, Abdullah A.. 2025. "Predicting near-real-time total water level with an artificial intelligence model based on Australia's tidal wave energy belt dataset." Journal of Ocean Engineering and Marine Energy. https://doi.org/10.1007/s40722-025-00394-wArticle
Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands
Chand, Ravinesh, Deo, Ravinesh C., Ghimire, Sujan, Nguyen-Huy, Thong and Ali, Mumtaz. 2025. "Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands." Stochastic Environmental Research and Risk Assessment. 39 (5), pp. 2203-2229. https://doi.org/10.1007/s00477-025-02964-8Article
Assessing Pan-Canada wildfire susceptibility by integrating satellite data with novel hybrid deep learning and black widow optimizer algorithms
Khosravi, Khabat, Mosallanejad, Ashkan, Bateni, Sayed M., Kim, Dongkyun, Jun, Changhyun, Shahvaran, Ali Reza, Farooque, Aitazaz A., Karbasi, Massoud and Ali, Mumtaz. 2025. "Assessing Pan-Canada wildfire susceptibility by integrating satellite data with novel hybrid deep learning and black widow optimizer algorithms." Science of the Total Environment. 977. https://doi.org/https://doi.org/10.1016/j.scitotenv.2025.179369Article
Exploring ChatGPT-Based Augmentation Strategies for Contrastive Aspect-Based Sentiment Analysis
Xu, Lingling, Xie, Haoran, Qin, S. Joe, Wang, Fu Lee and Tao, Xiaohui. 2025. "Exploring ChatGPT-Based Augmentation Strategies for Contrastive Aspect-Based Sentiment Analysis." IEEE Intelligent Systems. 40 (1), pp. 69-76. https://doi.org/10.1109/MIS.2024.3508432Article
Deep learning models for drought susceptibility mapping in Southeast Queensland, Australia
Rezaie, Fatemeh, Panahi, Mahdi P, Jun, Changhyun, Dayal, Kavina, Kim, Dongkyun, Darabi, Hamid, Kalantari, Zahra, Seifollahi-Aghmiuni, Samaneh, Deo, Ravinesh C. and Bateni, Sayed M.. 2025. "Deep learning models for drought susceptibility mapping in Southeast Queensland, Australia." Stochastic Environmental Research and Risk Assessment. https://doi.org/10.1007/s00477-024-02879-wArticle
A Dual-Stream Deep Learning Architecture With Adaptive Random Vector Functional Link for Multi-Center Ischemic Stroke Classification
Inamdar, Mahesh Anil, Gudigar, Anjan, Raghavendra, U., Salvi, Massimo, Aman, Raja Rizal Azman Bin Raja, Muhammad Gowdh, Nadia Fareeda, Ahir, Izzah Amirah Binti Mohd, Bin Kamaruddin, Mohd Salahuddin, Kadir, Khairul Azmi Abdul, Molinari, Filippo, Hegde, Ajay, Menon, Girish R. and Acharya, U. Rajendra. 2025. "A Dual-Stream Deep Learning Architecture With Adaptive Random Vector Functional Link for Multi-Center Ischemic Stroke Classification." IEEE Access. 13, pp. 46638-46658. https://doi.org/10.1109/ACCESS.2025.3550344Article
Application of transfer learning for biomedical signals: A comprehensive review of the last decade (2014–2024)
Jafari, Mahboobeh, Tao, Xiaohui, Barua, Prabal, Tan, Ru-San and Acharya, U.Rajendra. 2025. "Application of transfer learning for biomedical signals: A comprehensive review of the last decade (2014–2024)." Information Fusion. 118. https://doi.org/10.1016/j.inffus.2025.102982Article
Electricity demand uncertainty modeling with Temporal Convolution Neural Network models
Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David, Salcedo-Sanz, Sancho, Acharya, Rajendra and Dinh, Toan. 2025. "Electricity demand uncertainty modeling with Temporal Convolution Neural Network models." Renewable and Sustainable Energy Reviews. 209. https://doi.org/10.1016/j.rser.2024.115097Article
HebCGNN: Hebbian-enabled causal classification integrating dynamic impact valuing
Job, Simi, Tao, Xiaohui, Cai, Taotao, Li, Lin, Xie, Haoran, Xu, Cai and Yong, Jianming. 2025. "HebCGNN: Hebbian-enabled causal classification integrating dynamic impact valuing." Knowledge-Based Systems. 311. https://doi.org/10.1016/j.knosys.2025.113094Article
Explainable hybrid deep learning framework for enhancing multi-step solar ultraviolet-B radiation predictions
Prasad, Salvin S., Joseph, Lionel P., Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J., Acharya, Rajendra and Yaseen, Zaher M.. 2025. "Explainable hybrid deep learning framework for enhancing multi-step solar ultraviolet-B radiation predictions." Atmospheric Environment. 343. https://doi.org/10.1016/j.atmosenv.2024.120951Article
Perceived MOOC satisfaction: A review mining approach using machine learning and fine-tuned BERTs
Chen, Xieling, Xie, Haoran, Zou, Di, Cheng, Gary, Tao, Xiaohui and Wang, Fu Lee. 2025. "Perceived MOOC satisfaction: A review mining approach using machine learning and fine-tuned BERTs." Computers and Education: Artificial Intelligence. 8. https://doi.org/10.1016/j.caeai.2025.100366Article
Enhanced water quality prediction model using advanced hybridized resampling alternating tree-based and deep learning algorithms
Khosravi, Khabat, Farooque, Aitazaz Ahsan, Karbasi, Masoud, Ali, Mumtaz, Heddam, Salim, Faghfouri, Ali and Abolfathi, Soroush. 2025. "Enhanced water quality prediction model using advanced hybridized resampling alternating tree-based and deep learning algorithms." Environmental Science and Pollution Research. 32 (11), pp. 6405-6424. https://doi.org/10.1007/s11356-025-36062-7Article
A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting
Ahmadianfar, Iman, Farooque, Aitazaz Ahsan, Ali, Mumtaz, Jamei, Mehdi, Jamei, Mozhdeh and Yaseen, Zaher Mundher. 2025. "A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting." Scientific Reports. 15. https://doi.org/10.1038/s41598-025-90628-6Article
Systematic Review of AI and Machine Learning Approaches for Predicting Crop Diseases in the Context of Climate Change and the Food Security
Kaur, Avneet, Randhawa, Gurjit S., Farooque, Aitazaz A., Singh, Rajandeep, Ali, Mumtaz and Zaman, Qamar U.. 2025. "Systematic Review of AI and Machine Learning Approaches for Predicting Crop Diseases in the Context of Climate Change and the Food Security." Filho, Walter Leal, Matandirotya, Newton, Ayal, Desalegn Yayeh, Luetz, Johannes M. and Borsari, Bruno (ed.) Climate Change, Food Security, and Land Management: Strategies for a Sustainable Future. Switzerland. Springer. pp. 1-20Edited book (chapter)
Designing empirical fourier decomposition reinforced with multiscale increment entropy and deep learning to forecast dry bulb air temperature
Diykh, Mohammed, Ali, Mumtaz, Labban, Abdulhaleem H., Prasad, Ramendra, Jamei, Mehdi, Abdulla, Shahab and Farooque, Aitazaz Ahsan. 2025. "Designing empirical fourier decomposition reinforced with multiscale increment entropy and deep learning to forecast dry bulb air temperature." Results in Engineering. 26. https://doi.org/10.1016/j.rineng.2025.104597Article
Layered Model Stacking: Enhancing DDoS Detection Through Advanced Ensemble Machine Learning Techniques
Haddad, Nabeel Mahdy, Sahi, Aqeel, Diykh, Mohammed, Aljbur, Kaled, Kutfan, Ali, Abdulla, Shahab and Al-Hraishawi, Hayder. 2025. "Layered Model Stacking: Enhancing DDoS Detection Through Advanced Ensemble Machine Learning Techniques ." Chen, F. (ed.) 2024 IEEE Region 10 Conference (TENCON 2024). Singapore 01 - 04 Dec 2024 IEEE. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/TENCON61640.2024.10902823Paper
Modelling soil physical and chemical properties using existing datasets across grain growing regions of Australia
Gajurel, Suman. 2025. Modelling soil physical and chemical properties using existing datasets across grain growing regions of Australia. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/zwv89PhD by Publication
An Explainable Predictive Approach for Investigation of Greenhouse Gas Emissions in Maritime Canada's Potato Agriculture
Jamei, Mehdi, Yaqoob, Nauman, Farooque, Aitazaz A., Ali, Mumtaz, Malik, Anurag, Esau, Travis J. and Hu, Yulin. 2025. "An Explainable Predictive Approach for Investigation of Greenhouse Gas Emissions in Maritime Canada's Potato Agriculture." Smart Agricultural Technology . 10. https://doi.org/10.1016/j.atech.2024.100709Article
Near real-time significant wave height prediction along the coastline of Queensland using advanced hybrid machine learning models
Khosravi, K., Ali, M. and Heddam, S.. 2025. "Near real-time significant wave height prediction along the coastline of Queensland using advanced hybrid machine learning models." International Journal of Environmental Science and Technology. 22 (7), pp. 5309-5326. https://doi.org/10.1007/s13762-024-05944-7Article
Bathymetric modelling for long-term monitoring of water dynamics of Ramsar-listed lakes using inundation frequency and photon-counting LiDAR data
Zhang, Zhenyu and Liu, Xiaoye. 2025. "Bathymetric modelling for long-term monitoring of water dynamics of Ramsar-listed lakes using inundation frequency and photon-counting LiDAR data." Ecohydrology and Hydrobiology. 25 (1), pp. 10-22. https://doi.org/10.1016/j.ecohyd.2023.10.003Article
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy
Shaik, Thanveer, Tao, Xiaohui, Xie, Haoran, Li, Lin, Zhu, Xiaofeng and Li, Qing. 2024. "Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy." IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2024.3486109Article
A Multi-Plane Decoupled Convolutional Network for EEG-Based Auditory Attention Detection
Huang, Wei, Mei, Jiahao, Wei, Shicheng and Wang, Huabin. 2024. "A Multi-Plane Decoupled Convolutional Network for EEG-Based Auditory Attention Detection." 2024 9th International Conference on Signal and Image Processing (ICSIP). Nanjing, China 12 - 14 Jul 2024 China. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICSIP61881.2024.10671502Paper
Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition
Rajapakshe, Thejan, Rana, Rajib, Khalifa, Sara and Schuller, Björn W.. 2024. "Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition." IEEE Access. 12, pp. 193101-193114. https://doi.org/10.1109/ACCESS.2024.3519761Article
A designed predictive modelling strategy based on data decomposition and machine learning to forecast solar radiation
Ali, Mumtaz, Prasad, Ramendra, Alamery, Salman and Farooque, Aitazaz Ahsan. 2024. "A designed predictive modelling strategy based on data decomposition and machine learning to forecast solar radiation." Results in Engineering. 24. https://doi.org/10.1016/j.rineng.2024.103607Article
Dual-Phase Neural Networks for Feature Extraction and Ensemble Learning for Recognizing Human Health Activities
Dhar, Joy, Rana, Kapil, Goyal, Puneet, Alavi, Azadeh, Rana, Rajib, Vo, Bao Quoc, Mishr, Sudeepta and Mistry, Sajib. 2024. "Dual-Phase Neural Networks for Feature Extraction and Ensemble Learning for Recognizing Human Health Activities." Applied Soft Computing. 169. https://doi.org/10.1016/j.asoc.2024.112550Article
Cutting through the hype: artificial intelligence for clinical decision support in psychiatry
Squires, Matthew. 2024. Cutting through the hype: artificial intelligence for clinical decision support in psychiatry. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/zqv3yPhD by Publication
Feasibility of Mental Health Triage Call Priority Prediction Using Machine Learning
Rana, Rajib, Higgins, Niall, Haque, Kazi Nazmul, Burke, Kylie, Turner, Kathryn and Stedman, Terry. 2024. "Feasibility of Mental Health Triage Call Priority Prediction Using Machine Learning." Nursing Reports. 14 (4), pp. 4162-4172. https://doi.org/10.3390/nursrep14040303Article
Mental Health Diagnosis From Voice Data Using Convolutional Neural Networks and Vision Transformers
Islam, Rafiul, Ahad, Md. Taimur, Ahmed, Faruk, Song, Bo and Li, Yan. 2024. "Mental Health Diagnosis From Voice Data Using Convolutional Neural Networks and Vision Transformers." Journal of Voice. https://doi.org/10.1016/j.jvoice.2024.10.010Article
Monitoring of Greenhouse Gas Emission Drivers in Atlantic Canadian Potato Production: A Robust Explainable Intelligent Glass-Box
Jamei, Mehdi, Hassan, Muhammad, Farooque, Aitazaz A., Ali, Mumtaz, Karbasi, Masoud, Randhawa, Gurjit, Yaseen, Zaher Mundher and Dwyer, Ross. 2024. "Monitoring of Greenhouse Gas Emission Drivers in Atlantic Canadian Potato Production: A Robust Explainable Intelligent Glass-Box." Results in Engineering. 24. https://doi.org/10.1016/j.rineng.2024.103297Article
Innovative Multi-Temporal Evapotranspiration Forecasting Using Empirical Fourier Decomposition and Bidirectional Long Short-Term Memory
Karbasi, Masoud, Ali, Mumtaz, Randhawa, Gurjit S., Jamei, Mehdi, Malik, Anurag, Hussain, Syed Hamid Hussain, Bos, Melanie, Zaman, Qamar and Farooque, Aitazaz Ahsan. 2024. "Innovative Multi-Temporal Evapotranspiration Forecasting Using Empirical Fourier Decomposition and Bidirectional Long Short-Term Memory." Smart Agricultural Technology . 9. https://doi.org/10.1016/j.atech.2024.100619Article