Machine Learning Enabled Quantitative Ultrasound Techniques for Tissue Differentiation
Journal Article
Thomson, H., Yang, S., & Cochran, S. (2022)
Machine Learning Enabled Quantitative Ultrasound Techniques for Tissue Differentiation. Journal of Medical Ultrasonics, 49, 517-528. https://doi.org/10.1007/s10396-022-01230-6
Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered via radio-frequency ultrasound data. This paper describes how to implement the m...
Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems
Journal Article
Zheng, C., Yang, S., Parra-Ullauri, J., Garcia-Dominguez, A., & Bencomo, N. (2022)
Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(3), 479 - 488. https://doi.org/10.1109/TETCI.2021.3082204
Multi-agent systems deliver highly resilient and adaptable solutions for common problems in telecommunications, aerospace, and industrial robotics. However, achieving an optim...
PCA-ANFIS based prediction for water Injection effectiveness cycle in oil fields.
Journal Article
Tian, Y., Liu, Y., Cheng, G., & Wang, Z. (2014)
PCA-ANFIS based prediction for water Injection effectiveness cycle in oil fields. Applied Mechanics and Materials, 530/53, 422-428. https://doi.org/10.4028/www.scientific.net/AMM.530-531.422
By proposing a numerical based method on PCA-ANFIS(Adaptive Neuro-Fuzzy Inference System), this paper is focusing on solving the problem of uncertain cycle of water injection ...
Heaven and Hell: visions for pervasive adaptation
Journal Article
Paechter, B., Pitt, J., Serbedzija, N., Michael, K., Willies, J., & Helgason, I. (2011)
Heaven and Hell: visions for pervasive adaptation. Procedia Computer Science, 7, 81-82. https://doi.org/10.1016/j.procs.2011.12.025
With everyday objects becoming increasingly smart and the “info-sphere” being enriched with nano-sensors and networked to computationally-enabled devices and services, the way...