4611. Machine learning
| Title | 4611. Machine learning |
|---|---|
| Parent | 46. Information and Computing Sciences |
Latest research outputs
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Automatic disparity search range estimation in deep learning stereo
Perera, Ruveen. 2021. Automatic disparity search range estimation in deep learning stereo. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/m0vj-5p57PhD Thesis
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
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. 2023. "Bathymetric modelling for long-term monitoring of water dynamics of Ramsar-listed lakes using inundation frequency and photon-counting LiDAR data." Ecohydrology and Hydrobiology. https://doi.org/10.1016/j.ecohyd.2023.10.003Article
Big Data Management in Drug–Drug Interaction: A Modern Deep Learning Approach for Smart Healthcare
Salman, Muhammad, Munawar, Hafiz Suliman, Latif, Khalid, Akram, Muhammad Waseem, Khan, Sara Imran and Ullah, Fahim. 2022. "Big Data Management in Drug–Drug Interaction: A Modern Deep Learning Approach for Smart Healthcare." Big Data and Cognitive Computing. 6 (1), pp. 1-17. https://doi.org/10.3390/bdcc6010030Article
Boruta extra tree-bidirectional long short-term memory model development for Pan evaporation forecasting: Investigation of arid climate condition
Karbasi, Masoud, Ali, Mumtaz, Bateni, Sayed M., Jun, Changhyun, Jamei, Mehdi and Yaseen, Zaher Mundher. 2024. "Boruta extra tree-bidirectional long short-term memory model development for Pan evaporation forecasting: Investigation of arid climate condition." Alexandria Engineering Journal. 86, pp. 425-442. https://doi.org/10.1016/j.aej.2023.11.061Article
Click go the students, click-click-click: the efficacy of a student response system for engaging students to improve feedback and performance
Mula, Joseph M. and Kavanagh, Marie. 2009. "Click go the students, click-click-click: the efficacy of a student response system for engaging students to improve feedback and performance." e-Journal of Business Education and Scholarship of Teaching. 3 (1), pp. 1-17.Article
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
Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong and Yaseen, Z.. 2020. "Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts." Journal of Hydrology. 584, pp. 1-15. https://doi.org/10.1016/j.jhydrol.2020.124647Article
Contrastive and attentive graph learning for multi-view clustering
Wang, Ru, Li, Lin, Tao, Xiaohui, Wang, Peipei and Liu, Peiyu. 2022. "Contrastive and attentive graph learning for multi-view clustering." Information Processing and Management. 59 (4), pp. 1-14. https://doi.org/10.1016/j.ipm.2022.102967Article
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
Controlling Prosody in End-to-End TTS: A Case Study on Contrastive Focus Generation
Latif, Siddique, Kim, Inyoung, Calapodescu, Ioan and Besacier, Laurent. 2021. "Controlling Prosody in End-to-End TTS: A Case Study on Contrastive Focus Generation." 25th Conference on Computational Natural Language Learning (CoNLL 2021). Punta Cana, Dominican Republic 10 - 11 Nov 2021 Stroudsburg, Pennsylvania. https://doi.org/10.18653/v1/2021.conll-1.42Paper
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
Decentralized Blockchain Network
Abduljabbar, Tamara Abdulmunim, Tao, Xiaohui, Zhang, Ji, Yong, Jianming and Zhou, Xujuan. 2023. "Decentralized Blockchain Network." 2022 Tenth International Conference on Advanced Cloud and Big Data (CBD). Guilin, China 04 - 05 Nov 2022 China. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/CBD58033.2022.00049Paper
Deep learning based sleep stage classification
Ji, Xiaopeng. 2023. Deep learning based sleep stage classification. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z4y9qPhD by Publication
Deep learning based sleep stage classification studies
Pei, Wei. 2023. Deep learning based sleep stage classification studies. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z7y01PhD by Publication
Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction
Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David, Salcedo-sanz, Sancho, Sharma, Ekta and Ali, Mumtaz. 2022. "Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction." Measurement. 202, pp. 1-22. https://doi.org/10.1016/j.measurement.2022.111759Article
Deep Learning Techniques for Automated Dementia Diagnosis Using Neuroimaging Modalities: A Systematic Review
Ozkan, Dilek, Katar, Oguzhan, Ak, Murat, Al-Antari, Mugahed A., Ak, Nehir Yasan, Yildirim, Ozal, Mir, Hasan S., Tan, Ru-San and Acharya, U. Rajendra. 2024. "Deep Learning Techniques for Automated Dementia Diagnosis Using Neuroimaging Modalities: A Systematic Review ." IEEE Access. 12, pp. 127879-127902. https://doi.org/10.1109/ACCESS.2024.3454709Article
Deep Learning-Assisted Sensitive 3C-SiC Sensor for Long-Term Monitoring of Physical Respiration
Tran, Thi Lap, Nguyen, Duy Van, Nguyen, Hung, Nguyen, Thi Phuoc Van, Song, Pingan, Deo, Ravinesh C, Moloney, Clint, Dao, Viet Dung, Nguyen, Nam-Trung and Dinh, Toan. 2024. "Deep Learning-Assisted Sensitive 3C-SiC Sensor for Long-Term Monitoring of Physical Respiration." Advanced Sensor Research. 3 (8). https://doi.org/10.1002/adsr.202300159Article
Deep Representation Learning for Speech Emotion Recognition
Latif, Siddique. 2022. Deep Representation Learning for Speech Emotion Recognition. PhD by Publication Doctor of Philosophy (DPHD). University of Southern Queensland. https://doi.org/10.26192/w8w00PhD by Publication
Demo Abstract: CScrypt - A Compressive-Sensing-Based Encryption Engine for the Internet of Things
Xue, Wanli, Luo, Chengwen, Rana, Rajib, Hu, Wen and Seneviratne, Aruna. 2016. "Demo Abstract: CScrypt - A Compressive-Sensing-Based Encryption Engine for the Internet of Things." 14th ACM Conference on Embedded Network Sensor Systems (SenSys '16). Stanford, Calif, USA 14 - 16 Nov 2016 https://doi.org/10.1145/2994551.2996525Paper
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
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
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
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
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
Developing an EEG-Based Emotion Recognition Using Ensemble Deep Learning Methods and Fusion of Brain Effective Connectivity Maps
Bagherzadeh, Sara, Shalbaf, Ahmad, Shoeibi, Afshin, Jafari, Mahboobeh, Tan, Ru-San and Acharya, U. Rajendra. 2024. "Developing an EEG-Based Emotion Recognition Using Ensemble Deep Learning Methods and Fusion of Brain Effective Connectivity Maps." IEEE Access. 12, pp. 50949-50965. https://doi.org/10.1109/ACCESS.2024.3384303Article
Development of a multi-fusion convolutional neural network (MF-CNN) for enhanced gastrointestinal disease diagnosis in endoscopy image analysis
Hossain, Tanzim, Shamrat, F M Javed Mehedi, Zhou, Xujuan, Mahmud, Imran, Mazumder, Md. Sakib Ali, Sharmin, Sharmin and Gururajan, Raj. 2024. "Development of a multi-fusion convolutional neural network (MF-CNN) for enhanced gastrointestinal disease diagnosis in endoscopy image analysis." PeerJ Computer Science. 10. https://doi.org/10.7717/PEERJ-CS.1950Article
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
Development of Advanced Computer Aid Model for Shear Strength of Concrete Slender Beam Prediction
Sharafati, Ahmad, Haghbin, Masoud, Aldlemy, Mohammed Suleman, Mussa, Mohamed H., Al Zand, Ahmed W., Ali, Mumtaz, Bhagat, Suraj Kumar, Al-Ansari, Nadhir and Yaseen, Zaher Mundher. 2020. "Development of Advanced Computer Aid Model for Shear Strength of Concrete Slender Beam Prediction." Applied Sciences. 10 (11), pp. 1-25. https://doi.org/10.3390/app10113811Article
Development of an enhanced bidirectional recurrent neural network combined with time-varying filter-based empirical mode decomposition to forecast weekly reference evapotranspiration
Karbasi, Masoud, Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Chu, Xuefeng, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher. 2023. "Development of an enhanced bidirectional recurrent neural network combined with time-varying filter-based empirical mode decomposition to forecast weekly reference evapotranspiration." Agricultural Water Management. 290. https://doi.org/10.1016/j.agwat.2023.108604Article
Development of data intelligent models for electricity demand forecasting: case studies in the state of Queensland, Australia
Al-Musaylh, Mohanad Shakir Khalid. 2020. Development of data intelligent models for electricity demand forecasting: case studies in the state of Queensland, Australia. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z7tb-4754PhD Thesis
Development of electroencephalogram (EEG) signals classification techniques
Al Ghayab, Hadi Ratham Ghayab. 2019. Development of electroencephalogram (EEG) signals classification techniques. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/QMHP-7J93PhD Thesis
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
Digital strategies for nitrogen management in grain production systems: lessons from multi-method assessment using on-farm experimentation
Colaco, A.F., Whelan, B.M., Bramley, R.G.V., Richetti, J., Fajardo, M., McCarthy, A.C., Perry, E.M., Bender, A., Leo, S., Fitzgerald, G.J. and Lawes, R.A.. 2024. "Digital strategies for nitrogen management in grain production systems: lessons from multi-method assessment using on-farm experimentation ." Precision Agriculture. 25 (2), pp. 983-1013. https://doi.org/10.1007/s11119-023-10102-zArticle
Discriminating the brain activities for brain–computer interface applications through the optimal allocation-based approach
Siuly, Siuly and Li, Yan. 2015. "Discriminating the brain activities for brain–computer interface applications through the optimal allocation-based approach." Neural Computing and Applications. 26 (4), pp. 799-811. https://doi.org/10.1007/s00521-014-1753-3Article
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
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
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
Dynamic Task Allocation For Robotic Edge System Resilience Using Deep Reinforcement Learning
Afrin, Mahbuba, Jin, Jiong, Rahman, Ashfaqur, Li, Shi, Tian, Yu-Chuv and Li, Yan. 2024. "Dynamic Task Allocation For Robotic Edge System Resilience Using Deep Reinforcement Learning." IEEE Transactions on Systems, Man and Cybernetics: Systems. 54 (3), pp. 1438-1450. https://doi.org/10.1109/TSMC.2023.3327959Article
Ear-phone: a context-aware noise mapping using smart phones
Rana, Rajib, Chou, Chun Tung, Bulusu, Nirupama, Kanhere, Salil and Hu, Wen. 2015. "Ear-phone: a context-aware noise mapping using smart phones." Pervasive and Mobile Computing. 17 (Part A), pp. 1-22. https://doi.org/10.1016/j.pmcj.2014.02.001Article