A

Abuhassan, Mohammad, Anwar, Tarique, Fuller-Tyszkiewicz, Matthew, Jarman, Hannah K., Shatte, Adrian, Liu, Chengfei, and Sukunesan, Suku (2023) Classification of Twitter users with eating disorder engagement: Learning from the biographies. Computers in Human Behaviour, 140. 107519.

Ahmad, Jameel, Zia, Muhammad Umer, Naqvi, Ijaz Haider, Chattha, Jawwad Nasar, Butt, Faran Awais, Huang, Tao, and Xiang, Wei (2023) Machine learning and blockchain technologies for cybersecurity in connected vehicles. WIREs Data Mining and Knowledge Discovery. e1515. (In Press)

B

Bhope, Rajas, Talele, Kiran, and Huang, Tao (2023) Adaptive Ambiance Mode For Noise Cancelling Headphones. In: Proceedings of the IEEE Industrial Electronics and Applications Conference. pp. 231-236. From: IEACon 2023: IEEE Industrial Electronics and Applications Conference, 6-7 November 2023, Penang, Malaysia.

C

Calvert, Brendan, Olsen, Alex, Whinney, James, and Rahimi Azghadi, Mostafa (2021) Robotic spot spraying of Harrisia cactus (Harrisia martinii) in grazing pastures of the Australian rangelands. Plants, 10 (10). 2054.

Chaturvedi, Iti, Satapathy, Ranjan, Cavallari, Sandro, and Cambria, Erik (2019) Fuzzy commonsense reasoning for multimodal sentiment analysis. Pattern Recognition Letters, 125. pp. 264-270.

Chaturvedi, Iti, Cavallari, Sandro, Cambria, Erik, and Zheng, Vincent (2017) Learning word vectors in Deep Walk using convolution. In: Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference. pp. 323-328. From: FLAIRS-30: 30th International Florida Artificial Intelligence Research Society Conference, 22-24 May 2017, Marco Island, FL, USA.

Chaturvedi, Iti, Cambria, Erik, and Vilares, David (2016) Lyapunov filtering of objectivity for Spanish sentiment model. In: Proceedings of the International Joint Conference on Neural Networks. pp. 4474-4481. From: IJCNN: 2016 International Joint Conference on Neural Networks, 24-29 July 2016, Vancouver, Canada.

D

Dang, Xiaobing, Xiang, Wei, Yuan, Lei, Yang, Yuan, Wang, Eric, and Huang, Tao (2023) Deep Unfolding Scheme for Grant-Free Massive-Access Vehicular Networks. IEEE Transactions on Intelligent Transportation Systems. (In Press)

F

Fu, Yanfang, Du, Yishuai, Cao, Zijian, Li, Qiang, and Xiang, Wei (2022) A deep learning model for network intrusion detection with imbalanced data. Electronics, 11 (6). 898.

H

Huang, Yi, and Song, Insu (2022) PhysioVec: A Multi-stage Deep-Learning Framework for Searching Online Health Information with Breath Sound. In: Proceedings of the 5th International Conference on Big Data and Artificial Intelligence. pp. 26-33. From: BDAI 2022: IEEE 5th International Conference on Big Data and Artificial Intelligence, 8-10 July 2022, Fuzhou, China.

Huang, Yi, and Song, Insu (2022) PhysioVec: IoT Biosignal Based Search Engine for Gastrointestinal Health. In: Proceedings of the 7th International Conference on Computational Intelligence and Applications. pp. 230-236. From: ICCIA 2022: IEEE 7th International Conference on Computational Intelligence and Applications, 24-26 June 2022, Nanjing, China.

Hussain, Emtiaz, Hasan, Mahmudul, Rahman, Md Anisur, Lee, Ickjai, Tamanna, Tasmi, and Parvez, Mohammed Zavid (2021) CoroDet: a deep learning based classification for COVID-19 detection using chest X-ray images. Chaos Solitons and Fractals, 142. 110495.

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Jahanbakht, Mohammad, Rahimi Azghadi, Mostafa, and Waltham, Nathan J. (2023) Semi-supervised and weakly-supervised deep neural networks and dataset for fish detection in turbid underwater videos. Ecological Informatics, 78. 102303.

Jahanbakht, Mohammad (2022) Deep learning for internet of underwater things and ocean data analytics. PhD thesis, James Cook University.

Jahanbakht, Mohammad, Xiang, Wei, Robson, Barbara, and Rahimi Azghadi, Mostafa (2022) Nitrogen prediction in the Great Barrier Reef using finite element analysis with deep neural networks. Environmental Modelling & Software, 150. 105311.

Jahanbakht, Mohammad, Xiang, Wei, and Rahimi Azghadi, Mostafa (2022) Sea surface temperature forecasting with ensemble of stacked deep neural networks. IEEE Geoscience and Remote Sensing Letters, 19. 1502605.

Jahanbakht, Mohammad, Xiang, Wei, and Azghadi, Mostafa Rahimi (2022) Sediment Prediction in the Great Barrier Reef using Vision Transformer with finite element analysis. Neural Networks, 152. pp. 311-321.

Jahanbakht, Mohammad, Xiang, Wei, Hanzo, Lajos, and Rahimi Azghadi, Mostafa (2021) Internet of underwater things and big marine data analytics — a comprehensive survey. IEEE Communications Surveys & Tutorials, 23 (2). pp. 904-956.

K

Kong, Zhengmin, Ouyang, Hui, Cao, Yiyuan, Huang, Tao, Ahn, Euijoon, Zhang, Maoqi, and Liu, Hunan (2023) Automated periodontitis bone loss diagnosis in panoramic radiographs using a bespoke two-stage detector. Computers in Biology and Medicine, 152. 106374.

L

Liu, Shuo, Kong, Zhengmin, Huang, Tao, Du, Yang, and Xiang, Wei (2024) An ADMM-LSTM framework for short-term load forecasting. Neural Networks, 173. 106150.

Liu, Jianan, Xiong, Weiyi, Bai, Liping, Xia, Yuxuan, Huang, Tao, Ouyang, Wanli, and Zhu, Bing (2023) Deep instance segmentation with automotive radar detection points. IEEE Transactions on Intelligent Vehicles, 8 (1). pp. 84-94.

Liu, Jianan, Zhao, Qiuchi, Xiong, Weiyi, Huang, Tao, Han, Qing-Long, and Zhu, Bing (2023) SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar. IEEE Transactions on Intelligent Vehicles. (In Press)

Langlois, Lucas A., Collier, Catherine J., and McKenzie, Len J. (2023) Subtidal seagrass detector: development of a deep learning seagrass detection and classification model for seagrass presence and density in diverse habitats from underwater photoquadrats. Frontiers in Marine Science, 10. 1197695.

Liu, Ke, Huang, Tao, and Guo, Zhaoxia (2022) Classification of Pathological Images of Skin Diseases Based on Deep Learning. In: Proceedings of the 4th International Conference on Data-driven Optimization of Complex Systems. From: DOCS 2022: 4th International Conference on Data-driven Optimization of Complex Systems, 28-30 October 2022, Chengdu, China.

Lammie, Corey, Eshraghian, Jason K., Li, Chenqi, Amirsoleimani, Amirali, Genov, Roman, Lu, Wei D., and Azghadi, Mostafa Rahimi (2022) Design Space Exploration of Dense and Sparse Mapping Schemes for RRAM Architectures. In: Proceedings of the IEEE International Symposium on Circuits and Systems. pp. 1107-1111. From: ISCAS 2022: IEEE International Symposium on Circuits and Systems, 27 May - 1 June 2022, Austin, TX, USA.

Lammie, Corey, Xiang, Wei, Linares-Barranco, Bernabé, and Rahimi Azghadi, Mostafa (2022) MemTorch: an open-source simulation framework for memristive deep learning systems. Neurocomputing, 485. pp. 124-133.

Li, Chenqi, Lammie, Corey, Dong, Xuening, Amirsoleimani, Amirali, Azghadi, Mostafa Rahimi, and Genov, Roman (2022) Seizure Detection and Prediction by Parallel Memristive Convolutional Neural Networks. IEEE Transactions on Biomedical Circuits and Systems, 16 (4). pp. 609-625.

Lammie, Corey (2022) Simulation and implementation of novel deep learning hardware architectures for resource constrained devices. PhD thesis, James Cook University.

Lammie, Corey, Rahimiazghadi, Mostafa, and Ielmini, Daniele (2021) Empirical metal-oxide RRAM device endurance and retention model for deep learning simulations. Semiconductor Science and Technology, 36 (6). 065003.

Lammie, Corey, Eshraghian, Jason K., Lu, Wei D., and Rahimi Azghadi, Mostafa (2021) Memristive stochastic computing for deep learning parameter optimization. IEEE Transactions on Circuits and Systems II: Express Briefs, 68 (5). pp. 1650-1654.

Lammie, Corey, Xiang, Wei, and Rahimi Aghadi, Mostafa (2021) Towards memristive deep learning systems for real-time mobile epileptic seizure prediction. In: Proceedings of the IEEE International Symposium on Circuits and Systems. From: ISCAS 2021: IEEE International Symposium on Circuits and Systems, 22-28 May 2021, Daegu, Korea.

Laradji, Issam H., Saleh, Alzayat, Rodriguez, Pau, Nowrouzezahrai, Derek, Rahimi Azghadi, Mostafa, and Vazquez, David (2021) Weakly supervised underwater fish segmentation using affinity LCFCN. Scientific Reports, 11. p. 17379.

Liu, Hong-Bin (2020) Predictive spatio-temporal modelling with neural networks. PhD thesis, James Cook University.

Liu, Hong-Bin, and Lee, Ickjai (2020) Towards realistic meteorological predictive learning using conditional GAN. IEEE Access, 8. pp. 93179-93186.

Liu, Hong-Bin, Wu, Hao, Sun, Weiwei, and Lee, Ickjai (2019) Spatio-temporal GRU for trajectory classification. In: Proceedings of the 19th IEEE International Conference on Data Mining. pp. 1228-1233. From: ICDM 2019: 19th IEEE International Conference on Data Mining, 8-11 November 2019, Beijng, China.

Liu, Hongbin, and Lee, Ickjai (2017) End-to-end trajectory transportation mode classification using Bi-LSTM recurrent neural network. In: Proceedings of the 12th International Conference on Intelligent Systems and Knowledge Engineering. 158. From: ISKE 2017: 12th International Conference on Intelligent Systems and Knowledge Engineering, 24-26 November 2017, Nanjing, China.

M

Madhukumar, Neethu, Wang, Eric, Zhang, Yi-Fan, and Xiang, Wei (2021) Consensus forecast of rainfall using hybrid climate learning model. IEEE Internet of Things Journal, 8 (9). pp. 7270-7278.

P

Pratikno, Heri, Ibrahim, Mohd Zamri, and Jusak, (2022) A novel fern-like lines detection using a hybrid of pre-trained convolutional neural network model and Frangi filter. Telkomnika, 20 (3). pp. 607-620.

Possemiers, Aidan, and Lee, Ickjai (2021) Evaluating deep learned voice compression for use in video games. Expert Systems with Applications, 181. 115180.

Poria, Soujanya, Chaturvedi, Iti, Cambria, Erik, and Hussian, Amir (2017) Convolutional MKL based multimodal emotion recognition and sentiment analysis. In: Proceedings of the 16th International Conference on Data Mining. pp. 439-448. From: ICDM 2016: 16th International Conference on Data Mining, 12-15 December 2016, Barcelona, Spain.

S

Saleh, Alzayat, Sheaves, Marcus, Jerry, Dean, and Rahimi Azghadi, Mostafa (2024) Applications of deep learning in fish habitat monitoring: A tutorial and survey. Expert Systems with Applications, 238. 121841.

Saleh, Alzayat, Sheaves, Marcus, and Rahimi Azghadi, Mostafa (2022) Computer vision and deep learning for fish classification in underwater habitats: A survey. Fish and Fisheries, 23 (4). pp. 977-999.

Schoenhoff, Kurt, Holdsworth, Jason, and Lee, Ickjai (2020) Efficient semantic segmentation through dense upscaling convolutions. In: Proceedings of the 3rd International Conference on Software Engineering and Information Management. pp. 244-248. From: ICSIM'20: 3rd International Conference on Software Engineering and Information Management, 12-15 January 2020, Sydney, NSW, Australia.

W

Wang, Hao, Ahn, Euijoon, and Kim, Jinman (2022) Self-Supervised Representation Learning Framework for Remote Physiological Measurement Using Spatiotemporal Augmentation Loss. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence (36) From: AAAI-22: 36th AAAI Conference on Artificial Intelligence, 22 February - 1 March 2022, Virtual.

Wen, Haoran, Du, Yang, Lim, Eng Gee, Wen, Huiqing, Yan, Ke, Li, Xingshuo, and Jiang, Lin (2022) A solar forecasting framework based on federated learning and distributed computing. Building and Environment, 225. 109556.

X

Xiong, Weiyi, Liu, Jianan, Huang, Tao, Han, Qing-Long, Xia, Yuxuan, and Zhu, Bing (2023) LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion. IEEE Transactions on Intelligent Vehicles. (In Press)

Xiong, Weiyi, Liu, Jianan, Xia, Yuxuan, Huang, Tao, Zhu, Bing, and Xiang, Wei (2022) Contrastive Learning for Automotive mmWave Radar Detection Points Based Instance Segmentation. In: Proceedings of the IEEE 25th International Conference on Intelligent Transportation Systems. pp. 1255-1261. From: ITSC 2022: IEEE 25th International Conference on Intelligent Transportation Systems, Macau, China, 8-12 October 2022.

Y

Young, Tom, Cambria, Erik, Chaturvedi, Iti, Zhou, Hao, Biswas, Subham, and Huang, Minlie (2018) Augmenting end-to-end dialogue systems with commonsense knowledge. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence. pp. 4970-4977. From: AAAI-18: 32nd AAAI Conference on Artificial Intelligence, 2-7 February 2018, New Orleans, LA, USA.

Yan, Ke, Wang, Xudong, Du, Yang, Jin, Ning, Huang, Haichao, and Zhou, Hangxia (2018) Multi-step short-term power consumption forecasting with a hybrid deep learning strategy. Energies, 11. 3089.

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Zia, Muhammad Umer, Xiang, Wei, Vitetta, G.M., and Huang, Tao (2023) Deep Learning for Parametric Channel Estimation in Massive MIMO Systems. IEEE Transactions on Vehicular Technology, 72 (4). 4157 -4167.

Zhang, Tim, Amirsoleimani, Amirali, Eshraghian, Jason K., Rahimi Azghadi, Mostafa, Genov, Roman, and Xia, Yu (2023) SSCAE: A Neuromorphic SNN Autoencoder for sc-RNA-seq Dimensionality Reduction. In: Proceedings of the IEEE International Symposium on Circuits and Systems. From: ISCAS 2023: IEEE International Symposium on Circuits and Systems, 21-25 May 2023, Monterey, CA, USA.

Zhou, Xi, Xiang, Wei, and Huang, Tao (2023) A novel neural network for improved in-hospital mortality prediction with irregular and incomplete multivariate data. Neural Networks. (In Press)

Zeng, Yongkang, Chen, Jingjing, Jin, Ning, Jin, Xiaoping, and Du, Yang (2022) Air quality forecasting with hybrid LSTM and extended stationary wavelet transform. Building and Environment, 213. 108822.

Zia, Muhammad Umer, Xiang, Wei, Huang, Tao, and Ijaz Haider, Naqvi (2022) Deep Learning-aided TR-UWB MIMO System. IEEE Transactions on Communications, 70 (10). pp. 6579-6588.

Zhou, Hangxia, Liu, Qian, Yan, Ke, and Du, Yang (2021) Deep learning enhanced solar energy forecasting with AI-driven IoT. Wireless Communications and Mobile Computing, 2021. 9249387.