4602. Artificial intelligence
| Title | 4602. Artificial intelligence |
|---|---|
| Parent | 46. Information and Computing Sciences |
Latest research outputs
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Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach
Jamei, Mehdi, Ali, Mumtaz, Karbasi, Masoud, Xiang, Yong, Ahmadianfar, Iman and Yaseen, Zaher Mundher. 2022. "Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach ." Applied Energy. 326, pp. 1-24. https://doi.org/10.1016/j.apenergy.2022.119925Article
Development and Validation of a Dynamic Tool to Predict Aggressive Patient Behaviours in Hospital Settings: Artificial Intelligence-Based Approaches
Gururajan, R, Kondalsamy-Chennakesavan, S, Zhou, X. and Boon, K. 2022. "Development and Validation of a Dynamic Tool to Predict Aggressive Patient Behaviours in Hospital Settings: Artificial Intelligence-Based Approaches." Royal Australian College of Physicians (RACP) Congress 2022. Sydney, Australia 15 - 19 May 2022 SAGE Publications Ltd.Other
Predicting Women with Postpartum Depression Symptoms Using Machine Learning Techniques
Gopalakrishnan, Abinaya, Venkataraman, Revathi, Gururajan, Raj, Zhou, Xujuan and Zhu, Guohun. 2022. "Predicting Women with Postpartum Depression Symptoms Using Machine Learning Techniques." Mathematics. 10 (23). https://doi.org/10.3390/math10234570Article
Artificial Intelligence and Clean Air: Development of Novel Algorithms with Machine Learning and Deep Learning
Sharma, Ekta. 2022. Artificial Intelligence and Clean Air: Development of Novel Algorithms with Machine Learning and Deep Learning. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7q7wPhD by Publication
Using machine learning based emulators for the sensitivity analysis of process-driven biophysical models
Johnston, David B.. 2022. Using machine learning based emulators for the sensitivity analysis of process-driven biophysical models. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7q78PhD Thesis
Development of Deep Learning Hybrid Models for Hydrological Predictions
Ahmed, Abul Abrar Masrur. 2022. Development of Deep Learning Hybrid Models for Hydrological Predictions. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7q5zPhD by Publication
Adaptive fault diagnosis and resolution system for enterprise data replication system using deep reinforcement learning
Wee, Chee Keong. 2022. Adaptive fault diagnosis and resolution system for enterprise data replication system using deep reinforcement learning. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7486PhD Thesis
Mining heterogeneous information graph for health status classification
Pham, Thuan, Tao, Xiaohui, Zhang, Ji, Yong, Jianming, Zhang, Wenping and Cai, Yi. 2018. "Mining heterogeneous information graph for health status classification." 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC 2018). Kaohsiung, Taiwan 12 - 14 Nov 2018 United States. https://doi.org/10.1109/BESC.2018.8697292Paper
Exploring the use of a network model in drug prescription support for dental clinics
Goh, Wee Pheng, Tao, Xiaohui, Zhang, Ji, Yong, Jianming, Qin, Yongrui, Goh, Elizabeth Zhixin and Hu, Aimin. 2018. "Exploring the use of a network model in drug prescription support for dental clinics." 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC 2018). Kaohsiung, Taiwan 12 - 14 Nov 2018 Piscataway, NJ, United States. https://doi.org/10.1109/BESC.2018.00042Paper
The altruistic robot: do what I want, not just what I say
Billingsley, Richard, Billingsley, John, Gardenfors, Peter, Peppas, Pavlos, Prade, Henri, Skillicorn, David and Williams, Mary-Anne. 2017. "The altruistic robot: do what I want, not just what I say." Moral, S., Pivert, O., Sánchez, D. and Marín, N. (ed.) 11th International Conference on Scalable Uncertainty Management (SUM 2017). Granada, Spain 04 - 06 Oct 2017 Germany. https://doi.org/10.1007/978-3-319-67582-4_11Paper
Hierarchical neural topic modeling with manifold regularization
Chen, Ziye, Ding, Cheng, Rao, Yanghui, Xie, Haoran, Tao, Xiaohui, Cheng, Gary and Wang, Fu Lee. 2021. "Hierarchical neural topic modeling with manifold regularization." World Wide Web. 24 (6), pp. 2139-2160. https://doi.org/10.1007/s11280-021-00963-7Article
Mobile-based learning of drug prescription for medical education using artificial intelligence techniques
Tao, Xiaohui, Goh, Wee Pheng, Zhang, Ji, Yong, Jianming, Goh, Elizabeth Zhixin and Oh, Xueling. 2021. "Mobile-based learning of drug prescription for medical education using artificial intelligence techniques." International Journal of Mobile Learning and Organisation. 15 (4), pp. 392-408. https://doi.org/10.1504/IJMLO.2021.118436Article
Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions
Tao, Hai, Al-Khafaji, Zainab S., Qi, Chongchong, Zounemat-Kermani, Mohammad, Kisi, Ozgur, Tiyasha, Tiyasha, Chau, Kwok-Wing, Nourani, Vahid, Melesse, Assefa M., Elhakeem, Mohamed, Farooque, Aitazaz Ahsan, Nejadhashemi, A. Pouyan, Khedher, Khaled Mohamed, Alawi, Omer A., Deo, Ravinesh C., Shahid, Shamsuddin, Singh, Vijay P. and Yaseen, Zaher Mundher. 2021. "Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions." Engineering Applications of Computational Fluid Mechanics. 15 (1), pp. 1585-1612. https://doi.org/10.1080/19942060.2021.1984992Article
Survey of Deep Representation Learning for Speech Emotion Recognition
Latif, Siddique, Rana, Rajib, Khalifa, Sara, Jurdak, Raja, Qadir, Junaid and Schuller, Bjorn. 2023. "Survey of Deep Representation Learning for Speech Emotion Recognition." IEEE Transactions on Affective Computing. 14 (2), pp. 1634-1654. https://doi.org/10.1109/TAFFC.2021.3114365Article
Application of Quantum Natural Language Processing for Language Translation
Abbaszade, Mina, Salari, Vahid, Mousavi, S. Shahin, Zomorodi, Mariam and Zhou, Xujuan. 2021. "Application of Quantum Natural Language Processing for Language Translation." IEEE Access. 9, pp. 130434-130448. https://doi.org/10.1109/ACCESS.2021.3108768Article
Guided Generative Adversarial Neural Network for Representation Learning and Audio Generation using Fewer Labelled Audio Data
Haque, Kazi Nazmul, Rana, Rajib, Liu, Jiajun, Hansen, John H. L., Cummins, Nicholas, Busso, Carlos and Schuller, Bjorn W.. 2021. "Guided Generative Adversarial Neural Network for Representation Learning and Audio Generation using Fewer Labelled Audio Data." IEEE ACM Transactions on Audio, Speech, and Language Processing. 29, pp. 2575-2590. https://doi.org/10.1109/TASLP.2021.3098764Article
A novel spectral entropy-based index for assessing the depth of anaesthesia
Ra, Jee Sook, Li, Tianning and Li, Yan. 2021. "A novel spectral entropy-based index for assessing the depth of anaesthesia." Brain Informatics. 8 (1). https://doi.org/10.1186/s40708-021-00130-8Article
Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier
Al-Salman, Wessam, Li, Yan and Wen, Peng. 2021. "Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier." Neuroscience Research. 172, pp. 26-40. https://doi.org/10.1016/j.neures.2021.03.012Article
Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Sankaran, Adarsh, Deo, Ravinesh C., Xiao, Fuyuan and Zhu, Shuyu. 2021. "Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia." Renewable Energy. 177, pp. 1033-1044. https://doi.org/10.1016/j.renene.2021.06.052Article
A preliminary study of the impact of lateral head orientations on the current distributions during tDCS
Song, Bo, Menezes de Oliveira, Marilia, Wang, Shuaifang, Li, Yan, Wen, Peng and Ahfock, Tony. 2019. "A preliminary study of the impact of lateral head orientations on the current distributions during tDCS." Liang, Peipeng, Goel, Vinod and Shan, Chunlei (ed.) 12th International Conference on Brain Informatics (BI 2019). Haikou, China 13 - 15 Dec 2019 Cham, Switzerland. https://doi.org/10.1007/978-3-030-37078-7_25Paper
Development of flood risk monitoring and forecasting system with artificial intelligence predictive models for community risk management in Fiji
Moishin, Mohammed. 2021. Development of flood risk monitoring and forecasting system with artificial intelligence predictive models for community risk management in Fiji. Masters Thesis Master of Science (Research). University of Southern Queensland. https://doi.org/10.26192/zwww-vw94Masters Thesis
Application of deep learning on UAV-based aerial images for flood detection
Munawar, Hafiz Suliman, Ullah, Fahim, Qayyum, Siddra and Heravi, Amirhossein. 2021. "Application of deep learning on UAV-based aerial images for flood detection." Smart Cities. 4 (3), pp. 1220-1243. https://doi.org/10.3390/smartcities4030065Article
Hybrid deep learning method for a week-ahead evapotranspiration forecasting
Ahmed, A. A. Masrur, Deo, Ravinesh C., Feng, Qi, Ghahramani, Afshin, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2022. "Hybrid deep learning method for a week-ahead evapotranspiration forecasting." Stochastic Environmental Research and Risk Assessment. 36 (3), pp. 831-849. https://doi.org/10.1007/s00477-021-02078-xArticle
Streamflow prediction using an integrated methodology based on convolutional neural network and long short‑term memory networks
Ghimire, Sujan, Yaseen, Zaher Mundher, Farooque, Aitazaz A., Deo, Ravinesh C., Zhang, Ji and Tao, Xiaohui. 2021. "Streamflow prediction using an integrated methodology based on convolutional neural network and long short‑term memory networks." Scientific Reports. 11, pp. 1-26. https://doi.org/10.1038/s41598-021-96751-4Article
An integrated systems model for sustainable agricultural development under changing climate: a case study in a coffee production system in Viet Nam
Pham, Yen Hoang. 2021. An integrated systems model for sustainable agricultural development under changing climate: a case study in a coffee production system in Viet Nam. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/dbty-kn67PhD Thesis
A Novel Real-time Depth of Anaesthesia Monitoring Method using Detrended Fluctuation Analysis and ANN
Chen, Xing and Wen, Paul. 2020. "A Novel Real-time Depth of Anaesthesia Monitoring Method using Detrended Fluctuation Analysis and ANN." 2020 5th International Conference on Biomedical Signal and Image Processing (ICBIP 2020). Suzhou, China 21 - 23 Aug 2020 New York, United States. https://doi.org/10.1145/3417519.3419403Paper
Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data
Ahmed, A. A. Masrur, Deo, Ravinesh C., Raj, Nawin, Ghahramani, Afshin, Feng, Qi, Yin, Zhenliang and Yang, Linshan. 2021. "Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data." Remote Sensing. 13 (4), pp. 1-30. https://doi.org/10.3390/rs13040554Article
LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios
Ahmed, A. A. Masrur, Deo, Ravinesh C., Ghahramani, Afshin, Raj, Nawin, Feng, Qi, Yin, Zhenliang and Yang, Linshan. 2021. "LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios." Stochastic Environmental Research and Risk Assessment. 35, pp. 1851-1881. https://doi.org/10.1007/s00477-021-01969-3Article
A new framework for classification of multi-category hand grasps using EMG signals
Miften, Firas Sabar, Diykh, Mohammed, Abdulla, Shahab, Siuly, Siuly, Green, Jonathan H. and Deo, Ravinesh C.. 2021. "A new framework for classification of multi-category hand grasps using EMG signals." Artificial Intelligence in Medicine. 112, pp. 1-14. https://doi.org/10.1016/j.artmed.2020.102005Article
Charge prediction modeling with interpretation enhancement driven by double-layer criminal system
Li, Lin, Zhao, Lingyun, Nai, Peiran and Tao, Xiaohui. 2022. "Charge prediction modeling with interpretation enhancement driven by double-layer criminal system." World Wide Web. 25 (1), pp. 381-400. https://doi.org/10.1007/s11280-021-00873-8Article
Using back-and-forth translation to create artificial augmented textual data for sentiment analysis models
Body, Thomas, Tao, Xiaohui, Li, Yuefeng, Li, Lin and Zhong, Ning. 2021. "Using back-and-forth translation to create artificial augmented textual data for sentiment analysis models." Expert Systems with Applications. 178, pp. 1-12. https://doi.org/10.1016/j.eswa.2021.115033Article
Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity
Ahmed, A. A. Masrur, Deo, Ravinesh C., Feng, Qi, Ghahramani, Afshin, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2021. "Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity." Journal of Hydrology. 599, pp. 1-23. https://doi.org/10.1016/j.jhydrol.2021.126350Article
Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models
Bayatvarkeshi, Maryam, Bhagat, Suraj Kumar, Mohammadi, Kourosh, Kisi, Ozgur, Farahani, M., Hasani, A., Deo, Ravinesh and Yaseen, Zaher Mundher. 2021. "Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models." Computers and Electronics in Agriculture. 185. https://doi.org/10.1016/j.compag.2021.106158Article
Automated major depressive disorder detection using melamine pattern with EEG signals
Aydemir, Emrah, Tuncer, Tucker, Dogan, Sengul, Gururajan, Raj and Acharya, U. Rajendra. 2021. "Automated major depressive disorder detection using melamine pattern with EEG signals." Applied Intelligence. 51, pp. 6449-6466. https://doi.org/10.1007/s10489-021-02426-yArticle
Automated interpretation of biopsy images for the detection of celiac disease using a machine learning approach
Koh, Joel En Wei, de Michele, Simona, Sudarshan, Vidya K., Jahmunah, V., Ciaccio, Edward J., Ooi, Chui Ping, Gururajan, Raj, Gururajan, Rashmi, Oh, Shu Lih, Lewis, Suzanne K., Green, Peter H., Bhagat, Govind and Acharya, U. Rajendra. 2021. "Automated interpretation of biopsy images for the detection of celiac disease using a machine learning approach." Computer Methods and Programs in Biomedicine. 203. https://doi.org/10.1016/j.cmpb.2021.106010Article
Development and evaluation of data-driven models for electricity demand forecasting in Queensland, Australia
Kumie, Tobias. 2020. Development and evaluation of data-driven models for electricity demand forecasting in Queensland, Australia. Masters Thesis Master of Science (Research). University of Southern Queensland. https://doi.org/10.26192/tr73-nb90Masters Thesis
Countering Intelligence Algorithms: Decision Theory, Design Choices and Counter-AI
Phillips, Peter J. and Pohl, Gabriela. 2021. "Countering Intelligence Algorithms: Decision Theory, Design Choices and Counter-AI." RUSI Journal. 165 (7), pp. 22-32. https://doi.org/10.1080/03071847.2021.1893126Article
Deep Architecture Enhancing Robustness to Noise, Adversarial Attacks, and Cross-corpus Setting for Speech Emotion Recognition
Latif, Siddique, Rana, Rajib, Khalifa, Sara, Jurdak, Raja and Schuller, Bjorn W.. 2020. "Deep Architecture Enhancing Robustness to Noise, Adversarial Attacks, and Cross-corpus Setting for Speech Emotion Recognition." 21st Annual Conference of the International Speech Communication Association: Cognitive Intelligence for Speech Processing (INTERSPEECH 2020). Shanghai, China 25 - 29 Oct 2020 France. https://doi.org/10.21437/Interspeech.2020-3190Paper
Augmenting Generative Adversarial Networks for Speech Emotion Recognition
Latif, Siddique, Asim, Muhammad, Rana, Rajib, Khalifa, Sara, Jurdak, Raja and Schuller, Bjorn W.. 2020. "Augmenting Generative Adversarial Networks for Speech Emotion Recognition." 21st Annual Conference of the International Speech Communication Association: Cognitive Intelligence for Speech Processing (INTERSPEECH 2020). Shanghai, China 25 - 29 Oct 2020 France. https://doi.org/10.21437/Interspeech.2020-3194Paper
Future IoT tools for COVID-19 contact tracing and prediction: A review of the state-of-the-science
Jahmunah, Vicnesh, Sudarshan, Vidya K., Oh, Shu Lih, Gururajan, Raj, Gururajan, Rashmi, Zhou, Xujuan, Tao, Xiaohui, Faust, Oliver, Ciaccio, Edward J., Ng, Kwan Hoong and Acharya, U. Rajendra. 2021. "Future IoT tools for COVID-19 contact tracing and prediction: A review of the state-of-the-science." International Journal of Imaging Systems and Technology. 31 (2), pp. 455-471. https://doi.org/10.1002/ima.22552Article
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460201. Artificial life and complex adaptive systems
460202. Autonomous agents and multiagent systems
460203. Evolutionary computation
460206. Knowledge representation and reasoning
460207. Modelling and simulation
460208. Natural language processing
460209. Planning and decision making