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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)

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.