4611. Machine learning
| Title | 4611. Machine learning |
|---|---|
| Parent | 46. Information and Computing Sciences |
Latest research outputs
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Hyperbolic Mutual Learning for Bundle Recommendation
Ke, Haole, Li, Lin, Wang, PeiPei, Yuan, Jingling and Tao, Xiaohui. 2023. "Hyperbolic Mutual Learning for Bundle Recommendation." 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023). Tianjin, China 17 - 20 Apr 2023 Switzerland . Springer. https://doi.org/10.1007/978-3-031-30672-3_28Paper
Contribution of Geometric Feature Analysis for Deep Learning Classification Algorithms of Urban LiDAR Data
Tarsha Kurdi, Fayez, Amakhchan, Wijdan, Gharineiat, Zahra, Boulaassal, Hakim and Kharki, Omar El. 2023. "Contribution of Geometric Feature Analysis for Deep Learning Classification Algorithms of Urban LiDAR Data." Sensors. 23 (17). https://doi.org/10.3390/s23177360Article
Dual-interactive fusion for code-mixed deep representation learning in tag recommendation
Li, Lin, Wang, Peipei, Zheng, Xinhao, Xie, Qing, Tao, Xiaohui and Velasquez, Juan D.. 2023. "Dual-interactive fusion for code-mixed deep representation learning in tag recommendation." Information Fusion. 99. https://doi.org/10.1016/j.inffus.2023.101862Article
3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning
Ji, Xiaopeng, Li, Yan and Wen, Peng. 2023. "3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning." IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, pp. 3513-3523. https://doi.org/10.1109/TNSRE.2023.3309542Article
Early detection of paediatric and adolescent obsessive–compulsive, separation anxiety and attention deficit hyperactivity disorder using machine learning algorithms
Haque, Umme Marzia, Kabir, Enamul and Khanam, Rasheda. 2023. "Early detection of paediatric and adolescent obsessive–compulsive, separation anxiety and attention deficit hyperactivity disorder using machine learning algorithms." Health Information Science and Systems. 11 (1), pp. 1-14. https://doi.org/10.1007/s13755-023-00232-zArticle
New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes
Ali, Mumtaz, Jamei, Mehdi, Prasad, Ramendra, Karbasi, Masoud, Xiang, Yong, Cai, Borui, Abdulla, Shahab, Farooque, Aitazaz Ahsan and Labban, Abdulhaleem H.. 2023. "New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes." Ecological Indicators. 155. https://doi.org/10.1016/j.ecolind.2023.111030Article
Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network
Shen, Mingkan, Wen, Peng, Song, Bo and Li, Yan. 2023. "Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network." Computers in Biology and Medicine. 160. https://doi.org/10.1016/j.compbiomed.2023.107022Article
Prediction of Water Quality in Reservoirs: A Comparative Assessment of Machine Learning and Deep Learning Approaches in the Case of Toowoomba, Queensland, Australia
Farzana, Syeda Zehan, Paudyal, Dev Raj, Chadalavada, Sreeni and Alam, Md Jahangir. 2023. "Prediction of Water Quality in Reservoirs: A Comparative Assessment of Machine Learning and Deep Learning Approaches in the Case of Toowoomba, Queensland, Australia." Geosciences. 13 (293). https://doi.org/10.3390/geosciences13100293Article
Mental stress recognition on the fly using neuroplasticity spiking neural networks
Weerasinghe, Mahima Milinda Alwis, Wang, Grace, Whalley, Jacqueline and Crook-Rumsey, Mark. 2023. "Mental stress recognition on the fly using neuroplasticity spiking neural networks." Scientific Reports. 13. https://doi.org/10.1038/s41598-023-34517-wArticle
Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation
Zheng, Zihao, Ali, Mumtaz, Jamei, Mehdi, Xiang, Yong, Abdulla, Shahab, Yaseen, Zaher Mundher and Farooque, Aitazaz A.. 2023. "Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation." Renewable and Sustainable Energy Reviews. 185. https://doi.org/10.1016/j.rser.2023.113645Article
Multitask Learning From Augmented Auxiliary Data for Improving Speech Emotion Recognition
Latif, Siddique, Rana, Rajib, Khalifa, Sara, Jurdak, Raja and Schuller, Bjorn W.. 2023. "Multitask Learning From Augmented Auxiliary Data for Improving Speech Emotion Recognition ." IEEE Transactions on Affective Computing. 14 (4), pp. 3164-3176. https://doi.org/10.1109/TAFFC.2022.3221749Article
Designing a decomposition-based multi-phase pre-processing strategy coupled with EDBi-LSTM deep learning approach for sediment load forecasting
Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Rai, Priya, Karbasi, Masoud, Farooque, Aitazaz A. and Yaseen, Zaher Mundher. 2023. "Designing a decomposition-based multi-phase pre-processing strategy coupled with EDBi-LSTM deep learning approach for sediment load forecasting." Ecological Indicators. 153. https://doi.org/10.1016/j.ecolind.2023.110478Article
Development of high-resolution gridded data for water availability identification through GRACE data downscaling: Development of machine learning models
Tao, Hai, Al-Sulttani, Ahmed H., Salih, Sinan Q., Mohammed, Mustafa K.A., Khan, Mohammad Amir, Beyaztas, Beste Hamiye, Ali, Mumtaz, Elsayed, Salah, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2023. "Development of high-resolution gridded data for water availability identification through GRACE data downscaling: Development of machine learning models." Atmospheric Research. 291. https://doi.org/10.1016/j.atmosres.2023.106815Article
Multi-step ahead hourly forecasting of air quality indices in Australia: Application of an optimal time-varying decomposition-based ensemble deep learning algorithm
Jamei, Mehdi, Ali, Mumtaz, Jun, Changhyun, Bateni, Sayed M., Karbasi, Masoud, Farooque, Aitazaz A. and Yaseen, Zaher Mundher. 2023. "Multi-step ahead hourly forecasting of air quality indices in Australia: Application of an optimal time-varying decomposition-based ensemble deep learning algorithm." Atmospheric Pollution Research. 14 (6). https://doi.org/10.1016/j.apr.2023.101752Article
Machine Learning Algorithms for High-Resolution Prediction of Spatiotemporal Distribution of Air Pollution from Meteorological and Soil Parameters
Tao, Hai, Jawad, Ali H., Shather, A.H., Al-Khafaji, Zainab Al, Rashid, Tarik A., Ali, Mumtaz, Al-Ansari, Nadhir Al, Marhoon, Haydar Abdulameer, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2023. "Machine Learning Algorithms for High-Resolution Prediction of Spatiotemporal Distribution of Air Pollution from Meteorological and Soil Parameters." Environment International. 175. https://doi.org/10.1016/j.envint.2023.107931Article
Surface water electrical conductivity and bicarbonate ion determination using a smart hybridization of optimal Boruta package with Elman recurrent neural network
Jamei, Mehdi, Ali, Mumtaz, Karimi, Bakhtiar, Karbasi, Masoud, Farooque, Aitataz Ahsan and Yaseen, Zaher Mundher. 2023. "Surface water electrical conductivity and bicarbonate ion determination using a smart hybridization of optimal Boruta package with Elman recurrent neural network." Process Safety and Environmental Protection. 174, pp. 115-134. https://doi.org/10.1016/j.psep.2023.03.062Article
A comprehensive investigation of wetting distribution pattern on sloping lands under drip irrigation: A new gradient boosting multi-filtering-based deep learning approach
Jamei, Mehdi, Karimi, Bakhtiar, Ali, Mumtaz, Alinazari, Fariba, Karbasi, Masoud, Maroufpoor, Eisa and Chu, Xuefeng. 2023. "A comprehensive investigation of wetting distribution pattern on sloping lands under drip irrigation: A new gradient boosting multi-filtering-based deep learning approach." Journal of Hydrology. 620 (Part A). https://doi.org/10.1016/j.jhydrol.2023.129402Article
A novel global solar exposure forecasting model based on air temperature: Designing a new multi-processing ensemble deep learning paradigm
Jamei, Mehdi, Karbasi, Masoud, Ali, Mumtaz, Malik, Anurag, Chu, Xuefeng and Yaseen, Zaher Mundher. 2023. "A novel global solar exposure forecasting model based on air temperature: Designing a new multi-processing ensemble deep learning paradigm." Expert Systems with Applications. 222. https://doi.org/10.1016/j.eswa.2023.119811Article
Real-time epilepsy seizure detection based on EEG using tunable-Q wavelet transform and convolutional neural network
Shen, Mingkan, Wen, Peng, Song, Bo and Li, Yan. 2023. "Real-time epilepsy seizure detection based on EEG using tunable-Q wavelet transform and convolutional neural network." Biomedical Signal Processing and Control. 82. https://doi.org/10.1016/j.bspc.2022.104566Article
Ensemble robust local mean decomposition integrated with random forest for short-term significant wave height forecasting
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Jamei, Mehdi and Yaseen, Zaher Mundher. 2023. "Ensemble robust local mean decomposition integrated with random forest for short-term significant wave height forecasting." Renewable Energy. 205, pp. 731-746. https://doi.org/10.1016/j.renene.2023.01.108Article
Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition
Diykh, Mohammed, Abdulla, Shahab, Deo, Ravinesh C, Siuly, Siuly and Ali, Mumtaz. 2023. "Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition." Computer Methods and Programs in Biomedicine. 229. https://doi.org/10.1016/j.cmpb.2022.107305Article
Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting
Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Karbasi, Masoud, Rai, Priya and Yaseen, Zaher Mundher. 2023. "Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting." Journal of Hydrology. 617 (Part C). https://doi.org/10.1016/j.jhydrol.2023.129105Article
A Machine Learning Framework for Early-Stage Detection of Autism Spectrum Disorders
Hasan, S. M. Mahedy, Uddin, Palash, Al Mamun, Md., Sharif, Muhammad Imran, Ulhaq, Anwaar and Krishnamoorthy, Govind. 2023. "A Machine Learning Framework for Early-Stage Detection of Autism Spectrum Disorders." IEEE Access. 11, pp. 15038-5057. https://doi.org/10.1109/ACCESS.2022.3232490Article
CNN Based Image Classification of Malicious UAVs
Brown, Jason, Gharineiat, Zahra and Raj, Nawin. 2023. "CNN Based Image Classification of Malicious UAVs." Applied Sciences. 13 (1), pp. 1-13. https://doi.org/10.3390/app13010240Article
Water quality management using hybrid machine learning and data mining algorithms: An indexing approach
Aslam, Bilal, Maqsoom, Ahsen, Cheema, Ali Hassan, Ullah, Fahim, Alharbi, Abdullah and Imran, Muhammad. 2022. "Water quality management using hybrid machine learning and data mining algorithms: An indexing approach." IEEE Access. 10, pp. 119692 - 119705. https://doi.org/10.1109/ACCESS.2022.3221430Article
Rules-Based and SVM-Q Methods With Multitapers and Convolution for Sleep EEG Stages Classification
Zapata, Ignacio A., Li, Yan and Wen, Peng. 2022. "Rules-Based and SVM-Q Methods With Multitapers and Convolution for Sleep EEG Stages Classification." IEEE Access. 10, pp. 71299-71310. https://doi.org/10.1109/ACCESS.2022.3188286Article
Modelling and Real-time Optimisation of Air Quality Predictions for Australia through Artificial Intelligence Algorithm
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra and Parisi, Alfio V.. 2019. "Modelling and Real-time Optimisation of Air Quality Predictions for Australia through Artificial Intelligence Algorithm." AMSI Optimise 2019. Perth, Australia 17 - 21 Jun 2019 Perth, Australia.Poster
Sleep stage classification in EEG signals using the clustering approach based probability distribution features coupled with classification algorithms
Al-Salman, Wessam, Li, Yan, Oudah, Atheer Y. and Almaged, Sadiq. 2023. "Sleep stage classification in EEG signals using the clustering approach based probability distribution features coupled with classification algorithms." Neuroscience Research. https://doi.org/10.1016/j.neures.2022.09.009Article
Detecting Depression Using Single-Channel EEG and Graph Methods
Zhu, Guohun, Qiu, Tong, Ding, Yi, Gao, Shang, Zhao, Nan, Liu, Feng, Zhou, Xujuan and Gururajan, Raj. 2022. "Detecting Depression Using Single-Channel EEG and Graph Methods." Mathematics. 10 (22), pp. 1-10. https://doi.org/10.3390/math10224177Article
Multimodality Information Fusion for Automated Machine Translation
Li, Lin, Tayir, Turghun, Han, Yifeng, Tao, Xiaohui and Velasquez, Juan D.. 2023. "Multimodality Information Fusion for Automated Machine Translation." Information Fusion. 91, pp. 352-363. https://doi.org/10.1016/j.inffus.2022.10.018Article
Self Supervised Adversarial Domain Adaptation for Cross-Corpus and Cross-Language Speech Emotion Recognition
Latif, Siddique, Rana, Rajib, Khalifa, Sara, Jurdak, Raja and Schuller, Bjorn. 2023. "Self Supervised Adversarial Domain Adaptation for Cross-Corpus and Cross-Language Speech Emotion Recognition." IEEE Transactions on Affective Computing. 14 (3), pp. 1912-1926. https://doi.org/10.1109/TAFFC.2022.3167013Article
Identifying informative tweets during a pandemic via a topic‑aware neural language model
Gao, Wang, Li, Lin, Tao, Xiaohui, Zhou, Jing and Tao, Jun. 2023. "Identifying informative tweets during a pandemic via a topic‑aware neural language model." World Wide Web. 26 (1), pp. 55-70. https://doi.org/10.1007/s11280-022-01034-1Article
Machinability of Polymeric Composites and Future Reinforcements — A Review
Shalwan, Abdullah, Alsaeed, Talal and Yousif, Belal. 2022. "Machinability of Polymeric Composites and Future Reinforcements — A Review." Journal of Materials Science and Chemical Engineering. 10 (5), pp. 40-72. https://doi.org/10.4236/msce.2022.105004Article
Emotion Intensity and its Control for Emotional Voice Conversion
Zhou, Kun, Sisman, Berrak, Rana, Rajib, Schuller, Bjorn W. and Li, Haizhou. 2023. "Emotion Intensity and its Control for Emotional Voice Conversion." IEEE Transactions on Affective Computing. 14 (1), pp. 31-48. https://doi.org/10.1109/TAFFC.2022.3175578Article
A survey on deep reinforcement learning for audio‑based applications
Latif, Siddique, Cuayahuitl, Heriberto, Pervez, Farrukh, Shamshad, Fahad, Ali, Hafiz Shehbaz and Cambria, Erik. 2023. "A survey on deep reinforcement learning for audio‑based applications." Artificial Intelligence Review: an international survey and tutorial journal. 56 (3), p. 2193–2240. https://doi.org/10.1007/s10462-022-10224-2Article
FedStack: Personalized Activity Monitoring using Stacked Federated Learning
Shaik, Thanveer, Tao, Xiaohui, Higgins, Niall, Gururajan, Raj, Li, Yuefeng, Zhou, Xujuan and Acharya, U Rajendra. 2022. "FedStack: Personalized Activity Monitoring using Stacked Federated Learning." Knowledge-Based Systems. 257, pp. 1-14. https://doi.org/10.1016/j.knosys.2022.109929Article
Smartphone apps under development to aid pest monitoring
McCarthy, Alison, Long, Derek and Grundy, Paul. 2020. "Smartphone apps under development to aid pest monitoring." GRDC Grains Research Update: Driving Profit Through Research. Goondiwindi, Australia 03 - 04 Mar 2020 Australia.Paper
Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing
Riaz, Farina, Abdulla, Shahab, Ni, Wei, Radfar, Mohsen, Deo, Ravinesh and Hopkins, Susan. 2022. "Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing." Quantum Australia Conference 2022. Online 23 - 25 Feb 2022 Toowoomba, Australia. https://doi.org/10.13140/RG.2.2.34754.66245Poster
A Novel Policy for Pre-trained Deep Reinforcement Learning for Speech Emotion Recognition
Rajapakshe, Thejan, Rana, Rajib, Khalifa, Sara, Liu, Jiajun and Schuller, Bjorn W. 2022. "A Novel Policy for Pre-trained Deep Reinforcement Learning for Speech Emotion Recognition." Abramson, David and Dinh, Minh Ngoc (ed.) 2022 Australasian Computer Science Week (ACSW 2022). Brisbane, Australia 14 - 17 Feb 2022 United States. https://doi.org/10.1145/3511616.3513104Paper
A Framework for Burnt Area Mapping and Evacuation Problem Using Aerial Imagery Analysis
Munawar, Hafiz Suliman, Gharineiat, Zahra, Akram, Junaid and Khan, Sara Imran. 2022. "A Framework for Burnt Area Mapping and Evacuation Problem Using Aerial Imagery Analysis." Fire. 5 (4), pp. 1-15. https://doi.org/10.3390/fire5040122Article