A

Arushi, Dillon, Roberto, and Teoh, Ai Ni (2021) Designing a Virtual Reality based serious game for training public speaking skills. In: [Presented at the International Research Conference on Information Technology Education]. From: ICITE 2021: International Research Conference on Information Technology Education, 7 May 2021, Clark, Philippines.

Arushi, Dillon, Roberto, and Teoh, Ai Ni (2021) Real-time stress detection model and voice analysis: an integrated VR based game for training public speaking skills. In: Proceedings of the 3rd IEEE Conference on Games. From: 3rd IEEE Conference on Games, 17-20 August 2021, Copenhagen, Denmark.

Ahn, Euijoon, Feng, Dagan, and Kim, Jinman (2021) A spatial guided self-supervised clustering network for medical image segmentation. In: Lecture Notes in Computer Science (12901) pp. 379-388. From: MICCAI 2021: International Conference on Medical Image Computing and Computer-Assisted Intervention, 27 September - 1 October 2021, Strasbourg, France.

Akbari, Mohammadreza, and Do, Thu Nguyen Anh (2021) A systematic review of machine learning in logistics and supply chain management: current trends and future directions. Benchmarking, 28 (10). pp. 2977-3005.

Ahn, Euijoon, Kumar, Ashnil, Fulham, Michael, Feng, Dagan, and Kim, Jinman (2020) Unsupervised domain adaptation to classify medical images using zero-bias convolutional auto-encoders and context-based feature augmentation. IEEE Transactions on Medical Imaging, 39 (7). pp. 2385-2394.

Ahn, Euijoon, Kumar, Ashnil, Fulham, Michael, Feng, Dagan, and Kim, Jinman (2019) Convolutional sparse kernel network for unsupervised medical image analysis. Medical Image Analysis, 56. pp. 140-151.

Ahn, Euijoon, Kim, Jinman, Rahman, Khairunnessa, Baldacchino, Tanya, and Baird, Christine (2018) Development of a risk predictive scoring system to identify patients at risk of representation to emergency department: a retrospective population-based analysis in Australia. BMJ Open, 8. e021323.

B

Bhandari, Abhishta, Marwah, Ravi, Smith, Justin, Nguyen, Duy, Bhatti, Asim, Lim, Chee Peng, and Lasocki, Arian (2022) Machine learning imaging applications in the differentiation of true tumour progression from treatment-related effects in brain tumours: A systematic review and meta-analysis. Journal of Medical Imaging and Radiation Oncology, 66 (6). pp. 781-797.

C

Crocker, Rose, Robson, Barbara, Ani, Chinenye, Anthony, Ken, and Iwanaga, Takuya (2024) Synthetic data for reef modelling. Ecological Informatics, 82. 102698.

D

Darwen, Paul J. (2023) Direction of the Difference between Bayesian Model Averaging and the Best-Fit Model on Scarce-Data Low-Correlation Churn Prediction. In: Lecture Notes in Artificial Intelligence (13995) pp. 210-223. From: ACIIDS 2023: 15th Asian Conference on Intelligent Information and Database Systems, 24-26 July 2023, Phuket, Thailand.

Darwen, Paul J. (2019) Bayesian model averaging for river flow prediction. Applied Intelligence, 49. pp. 103-111.

Darwen, Paul J. (2019) Cost-effective prediction in medicine and marketing: only the difference between Bayesian model averaging and the single best-fit model. In: Proceedings of the IEEE 31st International Conference on Tools for Artificial Intelligence. pp. 1274-1279. From: ICTAI 2019: IEEE 31st International Conference on Tools for Artificial Intelligence, 4-6 November 2019, Portland, OR, USA.

Du, Yang, Yan, Ke, Ren, Zixiao, and Xiao, Weidong (2018) Designing localized MPPT for PV systems using fuzzy-weighted extreme learning machine. Energies, 11 (10). 2615.

G

Gill, Jaskaran, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2022) Combining kinetic orders for efficient S-System modelling of gene regulatory network. BioSystems, 220. 104736.

Gamage, Hasini Nakulugamuwa, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2022) Ensemble Regression Modelling for Genetic Network Inference. In: Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology. From: CIBCB 2022: IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 15-17 August 2022, Ottawa, Canada.

Gamage, Hasini Nakulugamuwa, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2022) Filter feature selection based Boolean Modelling for Genetic Network Inference. BioSystems, 221. 104757.

Gill, Jaskaran, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2022) Integrating steady-state and dynamic gene expression data for improving genetic network modelling. In: Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology. From: CIBCB 2022: IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 15-17 August 2022, Ottawa, Canada.

I

Igoe, Damien P., Parisi, Alfio, and Downs, Nathan J. (2019) Cloud segmentation property extraction from total sky image repositories using Python. Instrumentation Science and Technology, 47 (5). pp. 522-534.

K

Konovalov, Dmitry A., Jahangard, Simindokht, and Schwarzkopf, Lin (2018) In situ cane toad recognition. In: Proceedings of the International Conference on Digital Image Computing. From: DICTA 2018: Digital Image Computing: techniques and applications, 10-13 December 2018, Canberra, ACT, Australia.

L

Lyu, Shiyang, Adegboye, Oyelola, Adhinugraha, Kiki, Emeto, Theophilus I., and Taniar, David (2023) COVID-19 Prevention Strategies for Victoria Students within Educational Facilities: An AI-Based Modelling Study. Healthcare, 11 (6).

Li, Junlu, and Wei, Yuxing (2022) Evaluation of the market acceptance of vehicles with Random Forest. In: Proceedings of the IEEE 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering. pp. 464-469. From: AEMCSE 2022: IEEE 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering, 22-24 April 2022, Wuhan, China.

Linardon, Jake, Fuller-Tyszkiewicz, Matthew, Shatte, Adrian, and Greenwood, Christopher J. (2022) An exploratory application of machine learning methods to optimize prediction of responsiveness to digital interventions for eating disorder symptoms. International Journal of Eating Disorders, 55 (6). pp. 845-850.

M

Maskell, Peter, Ryan, Matt, Karawita, Anjana, Hickson, R.I., and Golchin, Maryam (2023) Building a one-vs-all classifier for spatial prediction of detected pathogens. In: Proceedings of the 25th International Congress on Modelling and Simulation. pp. 560-566. From: MODSIM 2023: 25th International Congress on Modelling and Simulation, 9-14 July 2023, Darwin, NT, Australia.

Mustafa, Akram, and Rahimi Azghadi, Mostafa (2021) Automated machine learning for healthcare and clinical notes analysis. Computers, 10 (2). 24.

N

Napier, Thomas, Ahn, Euijoon, Allen-Ankins, Slade, and Lee, Ickjai (2023) An Optimised Grid Search Based Framework for Robust Large-Scale Natural Soundscape Classification. In: Lecture Notes in Computer Science (14471) pp. 468-479. From: AI 2023: 36th Australasian Joint Conference on Artificial Intelligence, 28 November - 1 December 2023, Brisbane, QLD, Australia.

R

Roelfsema, Chris M., Lyons, Mitchell, Murray, Nicholas, Kovacs, Eva M., Kennedy, Emma, Markey, Kathryn, Borrego-Acevedo, Rodney, Ordoñez Alvarez, Alexandra, Say, Chantel, Tudman, Paul, Roe, Meredith, Wolff, Jeremy, Traganos, Dimosthenis, Asner, Gregory P., Bambic, Brianna, Free, Brian, Fox, Helen E., Lieb, Zoe, and Phinn, Stuart R. (2021) Workflow for the generation of expert-derived training and validation data: a view to global scale habitat mapping. Frontiers in Marine Science, 8. 643381.

S

Sadeghi, Mehdi, Karimi, Mohammad Reza, Karim, Amir Hossein, Farshbaf, Nafiseh Ghorbanpour, Barzegar, Abolfazl, and Schmitz, Ulf (2023) Network-Based and Machine-Learning Approaches Identify Diagnostic and Prognostic Models for EMT-Type Gastric Tumors. Genes, 14 (750).

Saleh, Alzayat (2020) Developing deep learning methods for aquaculture applications. Masters (Research) thesis, James Cook University.

Saleh, Alzayat, Laradji, Issam H., Konovalov, Dmitry A., Bradley, Michael, Vazquez, David, and Sheaves, Marcus (2020) A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis. Scientific Reports, 10. 14671.

Sankupellay, Mangalam, and Konovalov, Dmitry (2018) Bird call recognition using deep convolutional neural network, ResNet-50. In: Proceedings of the Australian Acoustical Society Conference. 134. From: AAS2018: Acoustics 2018: hear to listen, 6-9 November 2018, Adelaide, SA, Australia.

Suwanwiwat, Hemmaphan, Das, Abhijit, Ferrer, Miguel, Pal, Umapada, and Blumenstein, Michael (2017) An automatic student verification system utilising off-line Thai name components. In: Proceedings of the International Conference on Digital Image Computing. pp. 826-831. From: DICTA 2017: International Conference on Digital Image Computing: Techniques and Applications, 29 November - 1 December 2017, Sydney, NSW, Australia.

Suwanwiwat, Hemmaphan, Pal, Umpanda, and Blumenstein, Michael (2016) An automatic off-line short answer assessment system using novel hybrid features. In: Proceedings of the International Conference on Digital Image Computing: Techniques and Applications. pp. 757-764. From: DICTA 2016: International Conference on Digital Image Computing: Techniques and Applications, 30 November - 2 December 2016, Gold Coast, QLD, Australia.

T

Tan, Yue, Zheng, Kan, and Lei, Lei (2019) An in-vehicle keyword spotting system with multi-source fusion for vehicle applications. In: Proceedings of the IEEE Wireless Communications and Networking Conference. 8885980. From: WCNC 2019: IEEE Wireless Communications and Networking Conference, 15-18 April 2019, Marrakesh, Morocco.

V

Vos, Gideon, Trinh, Kelly, Sarnyai, Zoltan, and Rahimi Azghadi, Mostafa (2023) Generalizable machine learning for stress monitoring from wearable devices: A systematic literature review. International Journal of Medical Informatics, 173. 105026.

W

Wang, Jing, Song, Guangqin, Liddell, Michael, Morellato, Patricia, Lee, Calvin K.F., Yang, Dedi, Alberton, Bruna, Detto, Matteo, Ma, Xuanlong, Zhao, Yingyi, Yeung, Henry C.H., Zhang, Hongsheng, Ng, Michael, Nelson, Bruce W., Huete, Alfredo, and Wu, Jin (2023) An ecologically-constrained deep learning model for tropical leaf phenology monitoring using PlanetScope satellites. Remote Sensing of Environment, 286. 113429.

X

Xia, Feng, Guo, Teng, Bai, Xiaomei, Shatte, Adrian, Liu, Zitao, and Tang, Jiliang (2022) SUMMER: Bias-aware Prediction of Graduate Employment Based on Educational Big Data. ACM/IMS Transactions on Data Science, 2 (4). 39.

Xie, Jie, Towsey, Michael, Zhang, Liang, Yasumiba, Kiyomi, Schwarzkopf, Lin, Zhang, Jinlang, and Roe, Paul (2016) Multiple-instance multiple-label learning for the classification of frog calls with acoustic event detection. Lecture Notes in Computer Science, 9680. pp. 220-230.

Y

Yang, Wei, Xiang, Wei, Yang, Yuan, and Cheng, Peng (2023) Optimizing Federated Learning With Deep Reinforcement Learning for Digital Twin Empowered Industrial IoT. IEEE Transactions on Industrial Informatics, 19 (2). pp. 1884-1893.

Yan, Ke, Du, Yang, and Ren, Zixiao (2019) MPPT perturbation optimization of photovoltaic power systems based on solar irradiance data classification. IEEE Transactions on Sustainable Energy, 10 (2). pp. 514-521.