Items where Subject is "46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461104 Neural networks"

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Number of items at this level: 13.


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.

Baker, Stephanie (2021) Development of machine learning schemes for use in non-invasive and continuous patient health monitoring. PhD thesis, James Cook University.


Chaturvedi, Iti, Ragusa, Edoardo, Gastaldo, Paolo, Zunino, Rodolfo, and Cambria, Erik (2018) Bayesian network based extreme learning machine for subjectivity detection. Journal of The Franklin Institute, 355 (4). pp. 1780-1797.


Efremova, Dina B., Sankupellay, Mangalam, and Konovalov, Dmitry A. (2019) Data-efficient classification of birdcall through Convolutional Neural Networks transfer learning. In: Proceedings of the International Conference on Digital Image Computing. pp. 294-301. From: DICTA 2019: International Conference on Digital Image Computing: Techniques and Applications, 2-4 December 2019, Perth, WA, Australia.


Garcia, J.A., Waszek, L., Tauzin, B., and Schmerr, N. (2021) Automatic identification of mantle seismic phases using a Convolutional Neural Network. Geophysical Research Letters, 48 (18). e2020GL091658.


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. (In Press)


Khan, Saud, Khan, Komal S., and Shin, Soo Young (2019) Symbol denoising in high order M-QAM using residual learning of deep CNN. In: Proceedings of the 16th IEEE Annual Consumer Communications & Networking Conference. 8651830. From: CCNC 2019: 16th IEEE Annual Consumer Communications & Networking Conference, 11-14 January 2019, Las Vegas, NV, USA.


Rahimiazghadi, Mostafa, Linares-Barranco, Bernabe, Abbott, Derek, and Leong, Philip (2017) A hybrid CMOS-memristor neuromorphic synapse. IEEE Transactions on Biomedical Circuits and Systems, 11 (2). pp. 434-444.


Uddamvathanak, Rom, Feng, Yang, Xulei, Yang, Das, Ankit Kumar, Shen, Yan, Salahuddin, Mohamed, Hussain, Shaista, and Chawla, Shailey (2018) Two-stage ensemble of Deep Convolutional Neural Networks for object recognition. In: Proceedings of the IEEE International Conference on Intelligent Rail Transportation. From: ICIRT 2018: IEEE International Conference on Intelligent Rail Transportation, 12-14 December 2018, Singapore.


Xiang, Wei, Huang, Tao, and Wan, Wanggen (2019) Machine learning based optimization for vehicle-to-infrastructure communications. Future Generation Computer Systems, 94. pp. 488-495.


Yang, Shuangming, Wang, Jiang, Zhang, Nan, Deng, Bin, Pang, Yanwei, and Rahimi Azghadi, Mostafa (2022) CerebelluMorphic: large-scale neuromorphic model and architecture for supervised motor learning. IEEE Transactions on Neural Networks and Learning Systems. (In Press)

Yang, Shuangming, Wang, Jiang, Deng, Bin, Rahimi Azghadi, Mostafa, and Linares-Barranco, Bernabe (2022) Neuromorphic context-dependent learning framework with fault-tolerant spike routing. IEEE Transactions on Neural Networks and Learning Systems. (In Press)

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.

This list was generated on Wed Aug 17 23:01:31 2022 AEST.