4602. Artificial intelligence
| Title | 4602. Artificial intelligence |
|---|---|
| Parent | 46. Information and Computing Sciences |
Latest research outputs
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Artificial Intelligence in the Interpretation of Videofluoroscopic Swallow Studies: Implications and Advances for Speech–Language Pathologists
Girardi, Anna M., Cardell, Elizabeth A. and Bird, Stephen P.. 2023. "Artificial Intelligence in the Interpretation of Videofluoroscopic Swallow Studies: Implications and Advances for Speech–Language Pathologists ." Big Data and Cognitive Computing. 7 (4). https://doi.org/10.3390/bdcc7040178Article
Artificial intelligence informed simulation of dissolved Inorganic Nitrogen from ungauged catchments to the Great Barrier Reef
O’Sullivan, Cherie. 2023. Artificial intelligence informed simulation of dissolved Inorganic Nitrogen from ungauged catchments to the Great Barrier Reef. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z6206PhD by Publication
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
Artificial intelligence-based fast and efficient hybrid approach for spatial modelling of soil electrical conductivity
Ghorbani, Mohammad Ali, Deo, Ravinesh C., Kashani, Mahsa H., Shahabi, Mahmoud and Ghorbani, Shahryar. 2019. "Artificial intelligence-based fast and efficient hybrid approach for spatial modelling of soil electrical conductivity." Soil and Tillage Research. 186, pp. 152-164. https://doi.org/10.1016/j.still.2018.09.012Article
Artificial Intelligence: what is it and what does it mean for cotton?
McCarthy, Alison. 2023. "Artificial Intelligence: what is it and what does it mean for cotton?" 2023 Australian Cotton Research Conference. Toowoomba 05 - 07 Sep 2023 Australia.Keynote
Artificial life possibilities: a Star Trek perspective
Baillie-de Byl, Penny. 2006. Artificial life possibilities: a Star Trek perspective. Hingham, MA. United States. Charles River Media.Authored book
Artificial neural networks for prediction of Steadman Heat Index
Chand, Bhuwan, Nguyen-Huy, Thong and Deo, Ravinesh C.. 2021. "Artificial neural networks for prediction of Steadman Heat Index." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 293-357Edited book (chapter)
Assessing water renewal time scales for marine environments from three-dimensional modelling: a case study for Hervey Bay, Australia
Ribbe, Joachim, Wolff, Jorg-Olaf, Staneva, Joanna and Grawe, Ulf. 2008. "Assessing water renewal time scales for marine environments from three-dimensional modelling: a case study for Hervey Bay, Australia." Environmental Modelling and Software. 23 (10-11), pp. 1217-1228. https://doi.org/10.1016/j.envsoft.2008.02.007Article
Assessment and Prediction of Sea Level and Coastal Wetland Changes in Small Islands Using Remote Sensing and Artificial Intelligence
Raj, Nawin and Pasfield-Neofitou, Sarah. 2024. "Assessment and Prediction of Sea Level and Coastal Wetland Changes in Small Islands Using Remote Sensing and Artificial Intelligence." Remote Sensing. 16 (3), p. 551. https://doi.org/https://doi.org/10.3390/rs16030551Article
Assessment and prediction of significant wave height using hybrid CNN-BiLSTM deep learning model for sustainable wave energy in Australia
Raj, Nawin and Prakash, Reema. 2024. "Assessment and prediction of significant wave height using hybrid CNN-BiLSTM deep learning model for sustainable wave energy in Australia." Sustainable Horizons . 11. https://doi.org/10.1016/j.horiz.2024.100098Article
Assistive technology: opportunities and implications
Horner, Barbara, Soar, Jeffrey and Koch, Bill. 2009. "Assistive technology: opportunities and implications." Nay, Rhonda and Garrett, Sally (ed.) Older people: issues and innovations in care, 3rd ed.. Sydney, Australia. Elsevier. pp. 391-412Edited book (chapter)
Attribute Selection Hybrid Network Model for risk factors analysis of postpartum depression using Social media
Gopalakrishnan, Abinaya, Gururajan, Raj, Venkataraman, Revathi, Zhou, Xujuan, Chan, Ka Chan, Saravanan, Arul and Sen, Maitrayee. 2023. "Attribute Selection Hybrid Network Model for risk factors analysis of postpartum depression using Social media." Brain Informatics. 10. https://doi.org/10.1186/s40708-023-00206-7Article
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
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
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 screening for distress: A perspective for the future
Rana, Rajib, Latif, Siddique, Gururajan, Raj, Gray, Anthony, Mackenzie, Geraldine, Humphris, Gerald and Dunn, Jeff. 2019. "Automated screening for distress: A perspective for the future." European Journal of Cancer Care. 28 (4). https://doi.org/10.1111/ecc.13033Article
Automatic construction of domain-specific sentiment lexicon for context sensitive opinion retrieval
Lau, Raymond Y. K., Zhang, Wenping and Tao, Xiaohui. 2012. "Automatic construction of domain-specific sentiment lexicon for context sensitive opinion retrieval." Zhou, Yanqun (ed.) 4th IEEE International Conference on Computer Science and Information Technology (ICCSIT 2011). Chengdu, China 10 - 12 Jun 2011 Singapore. https://doi.org/10.7763/IPCSITPaper
Automatic Text Summarization Using Fuzzy Inference
Jafari, Mehdi, Shahabi, Amir Shahab, Wang, Jing, Qin, Yongrui, Tao, Xiaohui and Gheisari, Mehdi. 2016. "Automatic Text Summarization Using Fuzzy Inference." 22nd IEEE International Conference on Automation and Computing (ICAC 2016). Colchester, United Kingdom 07 - 08 Sep 2016 United States. https://doi.org/10.1109/IConAC.2016.7604928Paper
Automation and control in surface irrigation systems: current status and expected future trends
Koech, Richard, Smith, Rod and Gillies, Malcolm. 2010. "Automation and control in surface irrigation systems: current status and expected future trends." Goh, Steven C. and Wang, Hao (ed.) 2010 Southern Region Engineering Conference (SREC 2010). Toowoomba, Australia 11 - 12 Nov 2010 Toowoomba, Australia.Paper
Bat algorithm for dam–reservoir operation
Ethteram, Mohammad, Mousavi, Sayed-Farhad, Karami, Hojat, Farzin, Saeed, Deo, Ravinesh, Othman, Faridah Binti, Chau, Kwok-Wing, Sarkamaryan, Saeed, Singh, Vijay P. and El-Shafie, Ahmed. 2018. "Bat algorithm for dam–reservoir operation." Environmental Earth Sciences. 77 (13), pp. 1-15. https://doi.org/10.1007/s12665-018-7662-5Article
Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction
Nguyen-Huy, Thong, Deo, Ravinesh C., Yaseen, Zaher Mundher, Mushtaq, Shahbaz and Prasad, Ramendra. 2021. "Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 29-47Edited book (chapter)
Best relays selection method for error-resilient 3-D video transmission
Alajel, Khalid Mohamed, Xiang, Wei and Sileh, Ibrahim Khalil. 2012. "Best relays selection method for error-resilient 3-D video transmission." Dutkiewicz, Eryk (ed.) 12th International Symposium on Communications and Information Technologies (ISCIT 2012). Gold Coast, Australia 02 - 05 Oct 2012 Piscataway, NJ. United States . https://doi.org/10.1109/ISCIT.2012.6380891Paper
Big data in engineering applications
Roy, Sanjiban Sekhar, Samui, Pijushi, Deo, Ravinesh and Ntalampiras, Stalampiras (ed.) 2018. Big data in engineering applications. Singapore. Springer.Edited book
Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms
Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms." Applied Energy. 316, pp. 1-25. https://doi.org/10.1016/j.apenergy.2022.119063Article
Boundary treatment for virtual leaf surfaces
Loch, Birgit, Belward, John A. and Hanan, Jim S.. 2003. "Boundary treatment for virtual leaf surfaces." GRAPHITE '03: Computer Graphics and Interactive Techniques in Australasia and South East Asia . Melbourne, Australia 11 - 14 Feb 2003 New York, NY, USA. https://doi.org/10.1145/604471.604525Paper
Brain network, modelling and corresponding EEG patterns for health and disease states
Al-Hossenat, Auhood Hadi Jabbar. 2020. Brain network, modelling and corresponding EEG patterns for health and disease states. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/7xxq-3k23PhD Thesis
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
Chromosome Encoding Schemes in Genetic Algorithms for the Flexible Job Shop Scheduling: A State-of-art Review Useful for Artificial Intelligence Applications
Xuewen, Huang, Islam, Sardar M. N. and Zhou, Yuxun. 2020. "Chromosome Encoding Schemes in Genetic Algorithms for the Flexible Job Shop Scheduling: A State-of-art Review Useful for Artificial Intelligence Applications." 2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA). Australia 25 - 27 Nov 2020 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/CITISIA50690.2020.9371789Paper
Class-Level Logit Perturbation
Li, Mengyang, Su, Fengguang, Wu, Ou and Zhang, Ji. 2023. "Class-Level Logit Perturbation." IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2023.3273355Article
Cloud Affected Solar UV Predictions with Three-Phase Wavelet Hybrid Convolutional Long Short-Term Memory Network Multi-Step Forecast System
Prasad, Salvin S., Deo, Ravinesh C., Downs, Nathan, Igoe, Damien, Parisi, Alfio V. and Soar, Jeffrey. 2022. "Cloud Affected Solar UV Predictions with Three-Phase Wavelet Hybrid Convolutional Long Short-Term Memory Network Multi-Step Forecast System." IEEE Access. 10, pp. 24704-24720. https://doi.org/10.1109/ACCESS.2022.3153475Article
Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression
Deo, Ravinesh C., Ahmed, A.A. Masrur, Casillas-Perez, David, Pourmousavi, S. Ali, Segal, Gary, Yu, Yanshan and Salcedo-sanz, Sancho. 2023. "Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression." Renewable Energy. 203, pp. 113-130. https://doi.org/10.1016/j.renene.2022.12.048Article
Community-diversity Driven Influence Maximization on Social Networks
Li, Jianxin, Cai, Taotao, Ke, Deng, Wang, Xinjue, Sellis, Timos and Xia, Feng. 2020. "Community-diversity Driven Influence Maximization on Social Networks." Information Systems. 92. https://doi.org/10.1016/j.is.2020.101522Article
Comparative study of hybrid-wavelet artificial intelligence models for monthly groundwater depth forecasting in extreme arid regions, Northwest China
Yu, Haijiao, Wen, Xiaohu, Feng, Qi, Deo, Ravinesh C., Si, Jianhua and Wu, Min. 2018. "Comparative study of hybrid-wavelet artificial intelligence models for monthly groundwater depth forecasting in extreme arid regions, Northwest China." Water Resources Management. 32 (1), pp. 301-323. https://doi.org/10.1007/s11269-017-1811-6Article
Comparison of CNN-based deep learning architectures for rice diseases classification
Ahad, Md Taimur, Li, Yan, Song, Bo and Bhuiyan, Touhid. 2023. "Comparison of CNN-based deep learning architectures for rice diseases classification." Artificial Intelligence in Agriculture. 9, pp. 22-35. https://doi.org/10.1016/j.aiia.2023.07.001Article
Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions and Research Directions
Fallah, Seyedeh Narjes, Deo, Ravinesh Chand, Shojafar, Mohammad, Conti, Mauro and Shamshirband, Shahaboddin. 2018. "Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions and Research Directions." Energies. 11 (3). https://doi.org/10.3390/en11030596Article
Concerns of ageing and interest in assistive technologies: convenience sampling of attendees at an aged care technology exhibition in China
Soar, Jeffrey and Su, Ying. 2014. "Concerns of ageing and interest in assistive technologies: convenience sampling of attendees at an aged care technology exhibition in China." Liu, Kecheng, Gulliver, Stephen R., Li, Weizi and Yu, Changrui (ed.) 15th IFIP WG 8.1 International Conference on Informatics and Semiotics in Organisations (ICISO 2014): Service Science and Knowledge Innovation. Shanghai, China 23 - 24 May 2014 New York, NY. United States. https://doi.org/10.1007/978-3-642-55355-4_43Paper
Constructing a knowledge-based heterogeneous information graph for medical health status classification
Pham, Thuan, Tao, Xiaohui, Zhang, Ji and Yong, Jianming. 2020. "Constructing a knowledge-based heterogeneous information graph for medical health status classification." Health Information Science and Systems. 8 (1). https://doi.org/10.1007/s13755-020-0100-6Article
Constructive interpretation in design thinking
Kelly, Nick and Gero, John. 2009. "Constructive interpretation in design thinking." Cagdas, G. and Colokoglu, B. (ed.) 27th Conference of the Association for Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2009): Computation: The New Realm of Architectural Design. Istanbul, Turkey 16 - 19 Sep 2009 Vienna, Austria.Paper
Context-driven mood mining
Rana, Rajib. 2016. "Context-driven mood mining." 14th International Conference on Mobile Systems, Applications, and Services (MobiSys 2016). Singapore 25 - 30 Jun 2016 United States. https://doi.org/10.1145/2938559.2938601Poster
Contribution of climate models and APSIM phenological parameters to uncertainties in spring wheat simulations: application of SUFI-2 algorithm in northeast Australia
Collins, Brian, Najeeb, Ullah, Luo, Qunying and Tan, Daniel K. Y.. 2022. "Contribution of climate models and APSIM phenological parameters to uncertainties in spring wheat simulations: application of SUFI-2 algorithm in northeast Australia." Journal of Agronomy and Crop Science. 208 (2), pp. 225-242. https://doi.org/10.1111/jac.12575Article
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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