A

Addanki, Kranthi, Holdsworth, Jason, Hardy, Dianna, and Myers, Trina (2024) A pilot study using academagogy to personalize adult learner experiences in blended learning. In: Proceedings of 2024 AIS SIGED European Conference on Information Systems Education Research. From: ECISER 2024: European Conference on Information Systems Education Research, 13-19 June 2024, Paphos, Cyprus.

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.

Adhikari, Surabhi, Thapa, Surendrabikram, Naseem, Usman, Lu, Hai Ya, Bharathy, Gnana, and Prasad, Mukesh (2023) Explainable hybrid word representations for sentiment analysis of financial news. Neural Networks, 164. pp. 115-123.

Addanki, Kranthi, and Linda, Corrin (2023) Unveiling the potential of Digital Twin technology for Higher Education. In: ASCILITE 2023 Conference Proceedings: People, Partnerships and Pedagogies. From: ASCILITE 2023: 40th International Conference on Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education, 3-6 December 2023, Christchurch, New Zealand.

Anwar, Tarique, Fuller-Tyszkiewicz, Matthew, Jarman, Hannah K, Abuhassan, Mohammad, Shatte, Adrian, Team, WIRED, and Sukunesan, Suku (2022) EDBase: Generating a Lexicon Base for Eating Disorders Via Social Media. IEEE Journal of Biomedical and Health Informatics, 26 (12). pp. 6116-6125.

Ahn, Euijoon, Kumar, Ashnil, Feng, Dagan, Fulham, Michael, and Kim, Jinman (2019) Unsupervised Deep Transfer Feature Learning for Medical Image Classification. In: Proceedings of the IEEE 16th International Symposium on Biomedical Imaging. pp. 1915-1918. From: ISB I2019: IEEE 16th International Symposium on Biomedical Imaging, 8-11 April 2019, Venice, Italy.

Ahn, Euijoon, Kim, Jinman, Bi, Lei, Kumar, Ashnil, Li, Changyang, Fulham, Michael, and Feng, David Dagan (2017) Saliency-Based Lesion Segmentation Via Background Detection in Dermoscopic Images. IEEE Journal of Biomedical and Health Informatics, 21 (6). pp. 1685-1693.

Ahn, Euijoon, Bi, Lei, Jung, Youn Hyun, Kim, Jinman, Li, Changyang, Fulham, Michael, and Feng, David Dagan (2015) Automated saliency-based lesion segmentation in dermoscopic images. In: Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. pp. 3009-3012. From: EMBC 2015: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 25-29 August 2015, Milan, Italy.

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.

Baker, Stephanie, and Xiang, Wei (2023) Artificial Intelligence of Things for Smarter Healthcare: A Survey of Advancements, Challenges, and Opportunities. IEEE Communications Surveys & Tutorials, 25 (2). pp. 1261-1293.

Baker, Stephanie, Huang, Zhi, and Philippa, Bronson (2023) Lightweight Neural Network For Spatiotemporal Filling of Data Gaps in Sea Surface Temperature Images. IEEE Transactions on Geoscience and Remote Sensing, 61. 4204310.

Baker, Stephanie, and Kandasamy, Yogavijayan (2023) Machine learning for understanding and predicting neurodevelopmental outcomes in premature infants: a systematic review. Pediatric Research, 93. pp. 293-299.

Baker, Stephanie, Yogavijayan, Thiviya, and Kandasamy, Yogavijayan (2023) Towards Non-Invasive and Continuous Blood Pressure Monitoring in Neonatal Intensive Care Using Artificial Intelligence: A Narrative Review. Healthcare, 11 (24). 3107.

Baker, Stephanie, Xiang, Wei, and Atkinson, Ian (2022) A computationally efficient CNN-LSTM neural network for estimation of blood pressure from features of electrocardiogram and photoplethysmogram waveforms. Knowledge Based Systems, 250. 109151.

Baker, Stephanie, Xiang, Wei, and Atkinson, Ian (2021) Determining respiratory rate from photoplethysmogram and electrocardiogram signals using respiratory quality indices and neural networks. PLoS ONE, 16 (4). e0249843.

Bennett, Mary K., Younes Cardenas, Nicolas, and Joyce, Karen E. (2020) Automating drone image processing to map coral reef substrates using Google Earth Engine. Drones, 4 (3). 50.

Bi, Lei, Kim, Jinman, Ahn, Euijoon, Kumar, Ashnil, Feng, Dagan, and Fulham, Michael (2019) Step-wise integration of deep class-specific learning for dermoscopic image segmentation. Pattern Recognition, 85. pp. 78-89.

Bi, Lei, Kim, Jinman, Ahn, Euijoon, Kumar, Ashnil, Fulham, Michael, and Feng, Dagan (2017) Dermoscopic image segmentation via multistage fully convolutional networks. IEEE Transactions on Biomedical Engineering, 64 (9). pp. 2065-2074.

Bi, Lei, Kim, Jinman, Ahn, Euijoon, Feng, Dagan, and Fulham, Michael (2016) Automated skin lesion segmentation via image-wise supervised learning and multi-scale superpixel based cellular automata. In: Proceedings of the 13th International Symposium on Biomedical Imaging. pp. 1059-1062. From: ISBI 2016: 13th International Symposium on Biomedical Imaging, 13-16 April 20216, Prague, Czech Republic.

Bi, Lei, Kim, Jinman, Ahn, Euijoon, Feng, Dagan, and Fulham, Michael (2016) Automatic melanoma detection via multi-scale lesion-biased representation and joint reverse classification. In: Proceedings of the 13th International Symposium on Biomedical Imaging (4) pp. 1055-1058. From: ISBI 2016: 13th International Symposium on Biomedical Imaging, 13-16 April 20216, Prague, Czech Republic.

C

Chaturvedi, Iti, Pandelea, Vlad, Cambria, Erik, Welsch, Roy, and Datta, Bithin (2024) Barrier Function to Skin Elasticity in Talking Head. Cognitive Computation. (In Press)

Chaturvedi, Iti, Satapathy, Ranjan, Lynch, Curtis, and Cambria, Erik (2024) Predicting word vectors for microtext. Expert Systems, 41 (8). e13589.

Cai, Zhengyu, Kalatehbali, Hamid Rahimian, Walters, Ben, Rahimi Azghadi, Mostafa, Amirsoleimani, Amirali, and Genov, Roman (2023) Spike Timing Dependent Gradient for Direct Training of Fast and Efficient Binarized Spiking Neural Networks. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 13 (4). pp. 1083-1093.

Chaturvedi, Iti, Cambria, Erik, and Welsch, Roy E. (2023) Teaching Simulations Supported by Artificial Intelligence in the Real World. Education Sciences, 13 (2). 187.

Chen, Qian, Ragusa, Edoardo, Chaturvedi, Iti, Cambria, Erik, and Zunino, Rodolfo (2023) Text-Image Sentiment Analysis. In: Lecture Notes in Computer Science (13397) pp. 169-180. From: CICLing 2018: 19th International Conference on Computational Linguistics and Intelligent Text Processing, 18–24 March 2018, Hanoi, Vietnam.

Chaturvedi, Iti, Chen, Qian, Welsch, Roy E., Thapa, Kishor, and Cambria, Erik (2022) Gaussian correction for Adversarial learning of Boundaries. Signal Processing-Image Communication, 109. 116841.

Chaturvedi, Iti, Cambria, Erik, Chen, Qian, and McConnell, Desmond (2022) Landmark calibration for facial expressions and fish classification. Signal, Image and Video Processing, 16 (2). pp. 377-384.

Chaturvedi, Iti, Noel, Tim, and Satapathy, Ranjan (2022) Speech Emotion Recognition Using Audio Matching. Electronics, 11 (23). 3943.

Chaturvedi, Iti, Ragusa, Edoardo, Gastaldo, Paolo, and Cambria, Erik (2020) COAL: convolutional online adaptation learning for opinion mining. In: International Conference on Data Mining. pp. 15-22. From: ICDMW 2020: International Conference on Data Mining, 17-20 November 2020, Sorrento, Italy.

D

Das, Abhijit, Suwanwiwat, Hemmaphan, and Pal, Umapada (2024) A novel multi-task learning technique for offline handwritten short answer spotting and recognition. Multimedia Tools and Applications, 83. pp. 53441-53465.

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, 24 (12). pp. 14443-14452.

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.

Ditton, Elizabeth Rose (2022) Artificial Intelligence for autonomous persona generation to shape tailored communications and products and incentivise disaster preparation behaviours. PhD thesis, James Cook University.

Ditton, Elizabeth, Swinbourne, Anne, and Myers, Trina (2022) Selecting a clustering algorithm: A semi-automated hyperparameter tuning framework for effective persona development. Array, 14. 100186.

E

EMCR Brain Sciences Network Working Group (2022) Riding on the Brain's back: Building a strong brain science research community. AQ-Australian Quarterly, 93 (2). pp. 24-30.

F

Forest, Elizabeth, Swinbourne, Anne, Myers, Trina, and Scovell, Mitchell (2021) Applying Semi-Automated Hyperparameter Tuning for Clustering Algorithms. In: [Presented at the 36th IEEE/ACM International Conference on Automated Software Engineering]. From: ASE 2021: 36th IEEE/ACM International Conference on Automated Software Engineering, 14-20 November 2021, Online.

H

Haider, Majumder, Peyal, Mahmudul Kabir, Huang, Tao, and Xiang, Wei (2024) Road crack avoidance: a convolutional neural network-based smart transportation system for intelligent vehicles. Journal of Intelligent Transportation Systems. (In Press)

Hamilton, John R., Tee, Sing What, and Maxwell, Stephen J. (2023) AI and Firm Competitiveness. In: Proceedings of the 23rd International Conference on Electronic Business (23) pp. 17-24. From: ICEB 2023: 23rd International Conference on Electronic Business, 19-23 October 2023, Chiayi, Taiwan.

Hussain, Sadam, Lafarga-Osuna, Yareth, Ali, Mansoor, Naseem, Usman, Ahmed, Masroor, and Tamez-Peña, Jose Gerardo (2023) Deep learning, radiomics and radiogenomics applications in the digital breast tomosynthesis: a systematic review. BMC Bioinformatics, 24 (1). 401.

Hu, Liang, Liu, Dora D., Zhang, Qi, Naseem, Usman, and Lai, Zhong Yuan (2023) Self-Supervised Learning for Multilevel Skeleton-Based Forgery Detection via Temporal-Causal Consistency of Actions. In: Proceedings of the AAAI Conference on Artificial Intelligence (37) pp. 844-853. From: AAAI-23: 37th AAAI Conference on Artificial Intelligence, 7-14 February 2023.

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.

J

Jooq, Mohammad Khaleqi Qaleh, Rahimi Azghadi, Mostafa, Behbahani, Fereshteh, Al-Shidaifat, Alaaddin, and Song, Hanjung (2023) High-Performance and Energy-Efficient Leaky Integrate-and-Fire Neuron and Spike Timing-Dependent Plasticity Circuits in 7nm FinFET Technology. IEEE Access, 11. pp. 133451-133459.

Ji, Junhui, Ren, Wei, and Naseem, Usman (2023) Identifying Creative Harmful Memes via Prompt based Approach. In: Proceedings of the ACM Web Conference 2023. pp. 3868-3872. From: WWW '23: The ACM Web Conference 2023, April 30 - May 4 2023, Austin, TX, USA.

Jiang, C., Yuan, Y., Gu, B., Ahn, E., Kim, J., Feng, D., Huang, Q., and Song, S. (2023) Preoperative prediction of microvascular invasion and perineural invasion in pancreatic ductal adenocarcinoma with 18F-FDG PET/CT radiomics analysis. Clinical Radiology, 78 (9). pp. 687-696.

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 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, Jonathan, Trinh, Kelly, Kathrine, Hammill, and Chia-Ming Chen, Carla (2024) Not All Frailty Assessments Are Created Equal: Comparability of Electronic Health Data-Based Frailty Assessments in Assessing Older People in Residential Care. Biological Research For Nursing. (In Press)

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.

Kandasamy, Yogavijayan, and Baker, Stephanie (2023) An Exploratory Review on the Potential of Artificial Intelligence for Early Detection of Acute Kidney Injury in Preterm Neonates. Diagnostics, 13 (18). 2865.

Kasthuriarachchy, Buddhika, Chetty, Madhu, Shatte, Adrian, and Walls, Darren (2023) Meaning-Sensitive Text Data Augmentation with Intelligent Masking. ACM Transactions on Intelligent Systems and Technology, 14 (6). 104.

Krishnamenon, Madhumenon, Tuladhar, Rabin, Rahimi Azghadi, Mostafa, Loughran, Jeffrey G., and Pandey, Govinda (2022) Digital twins and their significance in engineering asset management. In: Proceedings of the International Conference on Maintenance and Intelligent Asset Management. From: ICMIAM 2021: International Conference on Maintenance and Intelligent Asset Management, 12-15 December 2021, Ballarat, VIC, Australia.

Kasthuriarachchy, Buddhika, Chetty, Madhu, Shatte, Adrian, and Walls, Darren (2021) Cost Effective Annotation Framework Using Zero-Shot Text Classification. In: Proceedings of the 2021 International Joint Conference on Neural Networks. From: IJCNN: 2021 International Joint Conference on Neural Networks, 18-22 July 2021, Shenzhen, China.

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, Li Xian, Sun, Zhiyue, Xu, Kunpeng, and Chen, Chao (2024) AI-Driven Financial Analysis: Exploring ChatGPT’s Capabilities and Challenges. International Journal of Financial Studies, 12 (3). 60.

Liu, Jianan, Zhao, Qiuchi, Xiong, Weiyi, Huang, Tao, Han, Qing-Long, and Zhu, Bing (2024) SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar. IEEE Transactions on Intelligent Vehicles, 9 (1). pp. 799-812.

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).

Liu, Jiachang, Zhang, Qi, Shi, Chongyang, Naseem, Usman, Wang, Shoujin, Hu, Liang, and Tsang, Ivor W. (2023) Causal Intervention for Abstractive Related Work Generation. In: Findings of the Association for Computational Linguistics: EMNLP 2023. pp. 2148-2159. From: EMNLP 2023: Conference on Empirical Methods in Natural Language Processing, 6-10 December 2023, Singapore.

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, Dora D., Hu, Liang, Zhang, Qi, Ye, Tangwei, Naseem, Usman, and Lai, Zhong Yuan (2023) A Dynamics and Task Decoupled Reinforcement Learning Architecture for High-Efficiency Dynamic Target Intercept. In: Proceedings of the 37th AAAI Conference on Articicial Intelligence (37) pp. 12049-12057. From: 37th AAAI Conference on Artificial Intelligence, 7-14 February 2023, Washington, DC, USA.

Li, Jingjin, Chen, Chao, Rahimi Azghadi, Mostafa, Ghodosi, Hossein, Pan, Lei, and Zhang, Jun (2023) Security and privacy problems in voice assistant applications: A survey. Computers & Security, 134. 103448.

Li, Chenqi, Lammie, Corey, Amirsoleimani, Amirali, Rahimi Azghadi, Mostafa, and Genov, Roman (2023) Simulation of memristive crossbar arrays for seizure detection and prediction using parallel Convolutional Neural Networks [Formula presented]. Software Impacts, 15 (March). 100473.

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.

Lu, Zhigang, Asghar, Hassan Jameel, Kaafar, Mohamed Ali, Webb, Darren, and Dickinson, Peter (2022) A Differentially Private Framework for Deep Learning With Convexified Loss Functions. IEEE Transactions on Information Forensics and Security, 17. pp. 2151-2165.

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.

Lammie, Corey, Xiang, Wei, and Rahimiazghadi, Mostafa (2022) Modeling and simulating in-memory memristive deep learning systems: an overview of current efforts. Array, 13. 100116.

Liu, Sisi, and Lee, Ickjai (2021) Sequence encoding incorporated CNN model for Email document sentiment classification. Applied Soft Computing, 102. 107104.

M

Maltarollo, Thalya Fernanda Horsth, Strazzi-Sahyon, Henrico Badaoui, Rodrigues Amaral, Rodrigo, and Sivieri-Araújo, Gustavo (2024) Is the field of endodontics prepared to utilise ChatGPT? Australian Endodontic Journal, 50 (1). pp. 176-177.

Madanayake, Adikarige Randil Sanjeewa, Lee, Kyungmi, and Lee, Ickjai (2024) Spatio-Temporal Contact Mining for Multiple Trajectories-of-Interest. IEEE Access, 12. pp. 79458-79467.

Marino, S. (2023) Delivering Smart Warehousing in Australia. In: Proceedings of the 23rd International Conference on Electronic Business (23) pp. 131-138. From: ICEB 2023: 23rd International Conference on Electronic Business, 19-23 October 2023, Chiayi, Taiwan.

Masood, Anum, Naseem, Usman, and Nasim, Mehwish (2023) Fully Automated CAD System for Lung Cancer Detection and Classification Using 3D Residual U-Net with multi-Region Proposal Network (mRPN) in CT Images. In: Lecture Notes in Computer Science. pp. 29-39. From: CaPTion: 2nd International Workshop on Cancer Prevention through Early Detection, 12 October 2023, Vancouver, Canada.

N

Noor, Nurhafihz (2024) Artificial Intelligence Service Agents. In: Ratten, Vanessa, (ed.) Reference Module in Social Sciences. Elsevier Reference Collection . Elsevier.

Naseem, Usman, Khushi, Matloob, Kim, Jinman, and Dunn, Adam G. (2024) Hybrid Text Representation for Explainable Suicide Risk Identification on Social Media. IEEE Transactions on Computational Social Systems. (In Press)

Noor, Nurhafihz, and Sim, Karen S. (2024) Impact of AI on the Flower of Service Model in the Hospitality Industry. In: Correia, Ricardo, Martins, Márcio, and Fontes, Ruta, (eds.) AI Innovations for Travel and Tourism. IGI Global, Hershey, PA, USA, pp. 58-81.

Naseem, Usman, Khushi, Matloob, Dunn, Adam G., and Kim, Jinman (2024) K-PathVQA: Knowledge-Aware Multimodal Representation for Pathology Visual Question Answering. IEEE Journal of Biomedical and Health Informatics, 28 (4). pp. 1886-1895.

Naseem, Usman, Kim, Jinman, Khushi, Matloob, and Dunn, Adam G. (2023) Graph-Based Hierarchical Attention Network for Suicide Risk Detection on Social Media. In: Proceedings of the ACM Web Conference 2023. pp. 995-1003. From: WWW 2023: The ACM Web Conference 2023: Companion of The World Wide Web Conference, April 30 - May 4 2023, Austin, TX, USA.

Naseem, Usman, Kim, Jinman, Khushi, Matloob, and Dunn, Adam G. (2023) A Multimodal Framework for the Identification of Vaccine Critical Memes on Twitter. In: Proceedings of the 16th ACM International Conference on Web Search and Data Mining. pp. 706-714. From: WSDM '23: 16th ACM International Conference on Web Search and Data Mining, 27 February - 3 March 2023, Singapore.

Naseem, Usman, Khushi, Matloob, Kim, Jinman, and Dunn, Adam G. (2023) RHMD: A Real-World Dataset for Health Mention Classification on Reddit. IEEE Transactions on Computational Social Systems, 10 (5). pp. 2325-2334.

Naseem, Usman, Lee, Byoung Chan, Khushi, Matloob, Kim, Jinman, and Dunn, Adam G. (2022) Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Model. In: Proceedings of First Workshop on Efficient Benchmarking in NLP. pp. 22-31. From: NLP Power 2022: First Workshop on Efficient Benchmarking in NLP, 26 May 2022, Dublin, IRL.

Naseem, Usman, Dunn, Adam G., Khushi, Matloob, and Kim, Jinman (2022) Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT. BMC Bioinformatics, 23. 144.

Naseem, Usman, Dunn, Adam G., Kim, Jinman, and Khushi, Matloob (2022) Early Identification of Depression Severity Levels on Reddit Using Ordinal Classification. In: Proceedings of the ACM Web Conference 2022. pp. 2563-2572. From: WWW '22: the ACM Web Conference 2022, 25-29 April 2022, Lyon, France.

Naseem, Usman, Kim, Jinman, Khushi, Matloob, and Dunn, Adam G. (2022) Identification of Disease or Symptom terms in Reddit to Improve Health Mention Classification. In: Proceedings of the ACM Web Conference 2022. pp. 2573-2581. From: WWW '22: the ACM Web Conference 2022, 25-29 April 2022, Lyon, France.

Naseem, Usman, Kim, Jinman, Khushi, Matloob, and Dunn, Adam G. (2022) Robust Identification of Figurative Language in Personal Health Mentions on Twitter. IEEE Transactions on Artificial Intelligence, 4 (2). pp. 362-372.

Naseem, Usman, Khushi, Matloob, and Kim, Jinman (2022) Vision-Language Transformer for Interpretable Pathology Visual Question Answering. IEEE Journal of Biomedical and Health Informatics, 27 (4). pp. 1681-1690.

Naseem, Usman, Khushi, Matloob, Reddy, Vinay, Rajendran, Sakthivel, Razzak, Imran, and Kim, Jinman (2021) BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition. In: Proceedings of the 2021 International Joint Conference on Neural Networks. From: IJCNN: 2021 International Joint Conference on Neural Networks, 18-22 July 2021, Shenzhen, China.

Naseem, Usman, Razzak, Imran, Khushi, Matloob, Eklund, Peter W., and Kim, Jinman (2021) COVIDSenti: A Large-Scale Benchmark Twitter Data Set for COVID-19 Sentiment Analysis. IEEE Transactions on Computational Social Systems, 8 (4). pp. 1003-1015.

Naseem, Usman, Khushi, Matloob, Kim, Jinman, and Dunn, Adam (2021) Classifying vaccine sentiment tweets by modelling domain-specific representation and commonsense knowledge into context-aware attentive GRU. In: Proceedings of the 2021 International Joint Conference on Neural Networks. From: IJCNN: 2021 International Joint Conference on Neural Networks, 18-22 July 2021, Shenzhen, China.

Naseem, Usman, Razzak, Imran, Khan, Shah Khalid, and Prasad, Mukesh (2021) A Comprehensive Survey on Word Representation Models: From Classical to State-of-the-Art Word Representation Language Models. ACM Transactions on Asian and Low-Resource Language Information Processing, 20 (5). 74.

Naseem, Usman, Musial, Katarzyna, Eklund, Peter, and Prasad, Mukesh (2020) Biomedical Named-Entity Recognition by Hierarchically Fusing BioBERT Representations and Deep Contextual-Level Word-Embedding. In: Proceedings of the 2020 International Joint Conference on Neural Networks. From: IJCNN: 2020 International Joint Conference on Neural Networks, 19-24 July 2020, Glasgow, UK.

Naseem, Usman, Razzak, Imran, Eklund, Peter, and Musial, Katarzyna (2020) Towards Improved Deep Contextual Embedding for the identification of Irony and Sarcasm. In: Proceedings of the 2020 International Joint Conference on Neural Networks. From: IJCNN: 2020 International Joint Conference on Neural Networks, 19-24 July 2020, Glasgow, UK.

Naseem, Usman, Razzak, Imran, Musial, Katarzyna, and Imran, Muhammad (2020) Transformer based Deep Intelligent Contextual Embedding for Twitter sentiment analysis. Future Generation Computer Systems, 113. pp. 58-69.

Naseem, Usman, Razzak, Imran, and Eklund, Peter W. (2020) A survey of pre-processing techniques to improve short-text quality: a case study on hate speech detection on twitter. Multimedia Tools and Applications, 80. pp. 35239-35266.

Naseem, Usman, and Musial, Katarzyna (2019) DICE: Deep Intelligent Contextual Embedding for Twitter Sentiment Analysis. In: Proceedings of the 15th IAPR International Conference on Document Analysis and Recognition. pp. 953-958. From: ICDAR 2019: 15th IAPR International Conference on Document Analysis and Recognition, 20-25 September 2019, Sydney, NSW, Australia.

P

Pratikno, Heri, Ibrahim, Mohd Zamri, and Jusak, Jusak (2024) A novel women's ovulation prediction through salivary ferning using the box counting and deep learning. Bulletin of Electrical Engineering and Informatics, 13 (2). pp. 996-1006.

R

Rashid, Junaid, Kim, Jungeun, and Naseem, Usman (2023) Coherent Topic Modeling for Creative Multimodal Data on Social Media. In: Proceedings of the ACM Web Conference 2023. pp. 3923-3927. From: WWW 2023: The ACM Web Conference 2023, April 30 - May 4 2023, Austin, TX, USA.

Rashid, Junaid, Kim, Jungeun, and Naseem, Usman (2023) Incorporating Embedding to Topic Modeling for More Effective Short Text Analysis. In: Proceedings of the ACM Web Conference 2023. pp. 73-76. From: WWW 2023: The ACM Web Conference 2023: Companion of The World Wide Web Conference, April 30 - May 4 2023, Austin, TX, USA.

Rashid, Junaid, Kim, Jungeun, Hussain, Amir, and Naseem, Usman (2023) WETM: A word embedding-based topic model with modified collapsed Gibbs sampling for short text. Pattern Recognition Letters, 172. pp. 158-164.

S

Shi, Chongyang, Yin, Yijun, Zhang, Qi, Xiao, Liang, Naseem, Usman, Wang, Shoujin, and Hu, Liang (2023) Multiview Clickbait Detection via Jointly Modeling Subjective and Objective Preference. In: Findings of the Association for Computational Linguistics: EMNLP 2023. pp. 11807-11816. From: EMNLP 2023: Conference on Empirical Methods in Natural Language Processing, 6-10 December 2023, Singapore.

Saleh, Alzayat (2023) Novel deep learning architectures for marine and aquaculture applications. PhD thesis, James Cook University.

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.

Stevens, Hallam (2022) The business machine in biology: the commercialization of AI in the life science. IEEE Annals of the History of Computing, 44 (1). pp. 8-19.

T

Thapa, Surendrabikram, Maratha, Ashwarya, Hasib, Khan Md, Nasim, Mehwish, and Naseem, Usman (2023) Assessing Political Inclination of Bangla Language Models. In: Proceedings of the 1st Workshop on Bangla Language Processing. pp. 152-162. From: BLP 2023: First Workshop on Bangla Language Processing, 7 December 2023, Singapore.

Thapa, Surendrabikram, Jafri, Farhan Ahmad, Hürriyetoğlu, Ali, Vargas, Francielle, Lee, Roy Ka Wei, and Naseem, Usman (2023) Multimodal Hate Speech Event Detection - Shared Task 4. In: Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text. pp. 151-159. From: CASE 2023: 6thWorkshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text, 7 September 2023, Varna, Bulgaria.

Thapa, Surendrabikram, Shah, Aditya, Jafri, Farhan Ahmad, Naseem, Usman, and Razzak, Imran (2022) A Multi-Modal Dataset for Hate Speech Detection on Social Media: Case-study of Russia-Ukraine Conflict. In: Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text. From: CASE 2022: the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text, 7-8 December 2022, Abu Dhabi, United Arab Emirates.

Thapa, Surendrabikram, Adhikari, Surabhi, Naseem, Usman, Singh, Priyanka, Bharathy, Gnana, and Prasad, Mukesh (2020) Detecting Alzheimer's Disease by Exploiting Linguistic Information from Nepali Transcript. In: Communications in Computer and Information Science (1332) pp. 176-184. From: ICONIP 202: 27th International Conference on Neural Information Processing, 18-22 November 2020, Bangkok, Thailand.

V

Veeramani, Hariram, Thapa, Surendrabikram, and Naseem, Usman (2023) DialectNLU at NADI 2023 Shared Task: Transformer Based Multitask Approach Jointly Integrating Dialect and Machine Translation Tasks in Arabic. In: Proceedings of the 1st Arabic Natural Language Processing Conference. pp. 614-619. From: ArabicNLP 2023: 1st Arabic Natural Language Processing Conference, 7 December 2023, Singapore.

Veeramani, Hariram, Thapa, Surendrabikram, and Naseem, Usman (2023) KnowTellConvince at ArAIEval Shared Task: Disinformation and Persuasion Detection in Arabic using Similar and Contrastive Representation Alignment. In: Proceedings of the 1st Arabic Natural Language Processing Conference. pp. 519-524. From: ArabicNLP 2023: 1st Arabic Natural Language Processing Conference, 7 December 2023, Singapore.

Veeramani, Hariram, Thapa, Surendrabikram, and Naseem, Usman (2023) LowResourceNLU at BLP-2023 Task 1 & 2: Enhancing Sentiment Classification and Violence Incitement Detection in Bangla Through Aggregated Language Models. In: Proceedings of the 1st Workshop on Bangla Language Processing. pp. 273-278. From: BLP 2023: First Workshop on Bangla Language Processing, 7 December 2023, Singapore.

Veeramani, Hariram, Thapa, Surendrabikram, and Naseem, Usman (2023) Temporally Dynamic Session-Keyword Aware Sequential Recommendation System. In: Proceedings of the IEEE International Conference on Data Mining Workshops. pp. 157-164. From: ICDMW 2023: 23rd IEEE International Conference on Data Mining Workshops, 4 December 2023, Shanghai, China.

W

Walters, Ben, Lammie, Corey, Yang, Shuangming, Jacob, Mohan V., and Rahimi Azghadi, Mostafa (2024) Unsupervised character recognition with graphene memristive synapses. Neural Computing and Applications, 36. pp. 1569-1584.

Walters, B., Lammie, C., Eshraghian, J., Yakopcic, C., Taha, T., Genov, R., Jacob, M.V., Amirsoleimani, A., and Rahimi Azghadi, M. (2023) Memristive Devices for Neuromorphic and Deep Learning Applications. In: Zho, Ye, (ed.) Advanced Memory Technology: Functional Materials and Devices. Optical, Electronic and Magnetic Materials . Royal Society of Chemistry, London, United Kingdom, pp. 680-704.

Warren-Rhodes, Kimberley, Cabrol, Nathalie A., Phillips, Michael, Tebes-Cayo, Cinthya, Kalaitzis, Freddie, Ayma, Diego, Demergasso, Cecilia, Chong-Diaz, Guillermo, Lee, Kevin, Hinman, Nancy, Rhodes, Kevin L., Boyle, Linda Ng, Bishop, Janice L., Hofmann, Michael H., Hutchinson, Neil, Javiera, Camila, Moersch, Jeffrey, Mondro, Claire, Nofke, Nora, Parro, Victor, Rodriguez, Connie, Sobron, Pablo, Sarazzain, Philippe, Wettergreen, David, Zacny, Kris, and the SETI Institute NAI Team (2023) Orbit-to-ground framework to decode and predict biosignature patterns in terrestrial analogues. Nature Astronomy, 7. pp. 406-422.

Wang, Han, Prakash, Nirmalendu, Hoang, Nguyen Khoi, Hee, Ming Shan, Naseem, Usman, and Lee, Roy Ka Wei (2023) Prompting Large Language Models for Topic Modeling. In: Proceedings of the 2023 IEEE International Conference on Big Data. pp. 1236-1241. From: BigData 2023: 2023 IEEE International Conference on Big Data, 15-18 December 2023, Sorrento, Italy.

Walters, Ben, Jacob, Mohan V., Amirsoleimani, Amirali, and Rahimi Azghadi, Mostafa (2023) A Review of Graphene-Based Memristive Neuromorphic Devices and Circuits. Advanced Intelligent Systems, 5 (10). 2300136.

Wang, Wei-Chien, Ahn, Euijoon, Feng, Dagan, and Kim, Jinman (2023) A Review of Predictive and Contrastive Self-supervised Learning for Medical Images. Machine Intelligence Research, 20 (4). pp. 483-512.

White, Nathan (2022) The Hmong Medical Corpus: a biomedical corpus for a minority language. Language Resources and Evaluation, 56. pp. 1315-1332.

X

Xiong, Weiyi, Liu, Jianan, Huang, Tao, Han, Qing-Long, Xia, Yuxuan, and Zhu, Bing (2024) LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion. IEEE Transactions on Intelligent Vehicles, 9 (1). pp. 79-92.

Xing, Frank, Schuller, Bjorn, Chaturvedi, Iti, Cambria, Erik, and Hussain, Amir (2023) Guest Editorial Neurosymbolic AI for Sentiment Analysis. IEEE Transactions on Affective Computing, 14 (3). pp. 1711-1715.

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

Yang, Shuangming, Wang, Haowen, Pang, Yanwei, Rahimi Azghadi, Mostafa, and Linares-Barranco, Bernabe (2024) NADOL: Neuromorphic Architecture for Spike-driven Online Learning By Dendrites. IEEE Transactions on Biomedical Circuits and Systems, 18 (1). pp. 186-199.

Ye, Tangwei, Hu, Liang, Zhang, Qi, Lai, Zhong Yuan, Naseem, Usman, and Liu, Dora D. (2023) Show Me The Best Outfit for A Certain Scene: A Scene-aware Fashion Recommender System. In: Proceedings of the ACM Web Conference 2023. pp. 1172-1180. From: WWW '23: The ACM Web Conference 2023, April 30 - May 4 2023, Austin, TX, USA.

Yang, Shuangming, Gao, Tian, Wang, Jiang, Deng, Bin, Rahimiazghadi, Mostafa, Lei, Tao, and Linares-Barranco, Bernabe (2022) SAM: a unified self-adaptive multicompartmental spiking neuron model for learning with working memory. Frontiers in Neuroscience, 16. 850945.

Z

Zhang, Qi, Yang, Yayi, Shi, Chongyang, Lao, An, Hu, Liang, Wang, Shoujin, and Naseem, Usman (2024) Rumor Detection With Hierarchical Representation on Bipartite Ad Hoc Event Trees. IEEE Transactions on Neural Networks and Learning Systems. (In Press)

Zhou, Shijia, Ahn, Euijoon, Wang, Hao, Quinton, Ann, Kennedy, Narelle, Sridar, Pradeeba, Nanan, Ralph, and Kim, Jinman (2023) Improving Automatic Fetal Biometry Measurement with Swoosh Activation Function. In: Lecture Notes in Computer Science (14226) pp. 283-292. From: MICCAI 2023: 26th International Conference on Medical Image Computing and Computer Assisted Intervention, 8-12 October 2023, Vancouver, Canada.

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, 167. pp. 741-750.

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.