Dr Yuhua Li

2024

• Wang, H., Marshall, A., Jones, D. and Li, Y. 2024. Improving high-frequency details in cerebellum for brain MRI super-resolution. Presented at: Conference on ICT Solutions for eHealth (ICTS4eHealth 2024), Paris, France, 26 - 29 June 20242024 IEEE Symposium on Computers and Communications (ISCC). IEEE pp. 1-7., (10.1109/ISCC61673.2024.10733580)
• Zhang, M., Treder, M., Marshall, D. and Li, Y. 2024. Explaining the predictions of kernel SVM models for neuroimaging data analysis. Expert Systems with Applications 251, article number: 123993. (10.1016/j.eswa.2024.123993)
• Wu, F., Liu, A., Chen, J. and Li, Y. 2024. Analysing network dynamics: The contagion effects of SVB's collapse on the US tech industry. Journal of Risk and Financial Management 17(10), article number: 427. (10.3390/jrfm17100427)
• Zhang, M., Treder, M., Marshall, A. and Li, Y. 2024. Fast explanation of RBF-Kernel SVM models using activation patterns. Presented at: International Joint Conference on Neural Networks, Yokohama, Japan, 30 June – 5 July 2024Proceedings of IJCNN. IEEE pp. 1-8., (10.1109/IJCNN60899.2024.10650697)
• Alqurashi, N., Li, Y. and Sidorov, K. 2024. Improving speech emotion recognition through hierarchical classification and text integration for enhanced emotional analysis and contextual understanding. Presented at: International Joint Conference on Neural Networks, Yokohama, Japan, 30 June – 5 July 2024Proceedings of IJCNN. IEEE pp. 1-8., (10.1109/IJCNN60899.2024.10650087)
• Li, S., Li, Y. and Perera, C. 2024. Mobile sensing within smart buildings: A survey. Technical Report.
• Alqurashi, N., Li, Y., Sidorov, K. and Marshall, A. 2024. Decision fusion based multimodal hierarchical method for speech emotion recognition from audio and text. Presented at: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium, 9-11 October 2024.
• Lewis-Cheetham, J., Li, Y., Liberatore, F. and Wang, Q. 2024. The impact of transaction costs on forecast-based trading strategy performance. Presented at: CIFEr 2024: IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, Hoboken, New Jersey, USA, 22-23 October 2024.

2023

• Wang, H., Treder, M., Marshall, D., Jones, D. and Li, Y. 2023. A skewed loss function for correcting predictive bias in brain age prediction. IEEE Transactions on Medical Imaging 42(6), pp. 1577-1589. (10.1109/TMI.2022.3231730)
• Zhang, F., Zhao, H., Li, Y., Wu, Y. and Sun, X. 2023. CBA-GAN: Cartoonization style transformation based on the convolutional attention module. Computers and Electrical Engineering 106, article number: 108575. (10.1016/j.compeleceng.2022.108575)
• Anggoro, A. W., Corcoran, P., De Widt, D. and Li, Y. 2023. Using DistilBERT to assign HS codes to international trading transactions. Presented at: World Conference on Information Systems and Technologies, Pisa, Italy, 4 - 6 April 2023.

2022

• Sidorowicz, T., Peres, P. and Li, Y. 2022. A novel approach for cross-selling insurance products using positive unlabelled learning. Presented at: International Joint Conference on Neural Networks, Padua - Italy, 18-23 July 20222022 International Joint Conference on Neural Networks (IJCNN). IEEE, (10.1109/IJCNN55064.2022.9892762)
• Bent, G., Simpkin, C., Li, Y. and Preece, A. 2022. Energy efficient spiking neural network neuromorphic processing to enable decentralised service workflow composition in support of multi-domain operations. Presented at: SPIE Defense + Commercial Sensing 2022, Orlando, Florida, United States, 3 April - 13 June 2022 Presented at Pham, T. and Solomon, L. eds.Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, Vol. 12113. SPIE pp. 121131M., (10.1117/12.2617362)
• Bent, G., Simpkin, C., Li, Y. and Preece, A. 2022. Hyperdimensional computing using time-to-spike neuromorphic circuits. Presented at: 2022 IEEE World Congress on Computational Intelligence (WCCI), Padova, Italy, 18-23 July 2022. IEEE

2021

• Sohail, M., Peres, P. and Li, Y. 2021. Feature importance analysis for customer management of insurance products. Presented at: 2021 International Joint Conference on Neural Networks (IJCNN), Virtual, 18-22 July 2021.

2020

• Zhao, H., Zheng, J., Wang, Y., Yuan, X. and Li, Y. 2020. Portrait style transfer using deep convolutional neural networks and facial segmentation. Computers and Electrical Engineering 85, article number: 106655. (10.1016/j.compeleceng.2020.106655)
• Taherkhani, A., Belatreche, A., Li, Y., Cosma, G., Maguire, L. P. and McGinnity, T. 2020. A review of learning in biologically plausible spiking neural networks. Neural Networks 122, pp. 253-272. (10.1016/j.neunet.2019.09.036)

2018

• Taherkhani, A., Belatreche, A., Li, Y. and Maguire, L. P. 2018. A supervised learning algorithm for learning precise timing of multiple spikes in multilayer spiking neural networks. IEEE Transactions on Neural Networks and Learning Systems 29(11), pp. 5394-5407. (10.1109/TNNLS.2018.2797801)
• Liu, S. et al. 2018. Quantitative analysis of breast cancer diagnosis using a probabilistic modelling approach. Computers in Biology and Medicine 92, pp. 168-175. (10.1016/j.compbiomed.2017.11.014)

2017

• Shynkevich, Y., McGinnity, T., Coleman, S. A., Belatreche, A. and Li, Y. 2017. Forecasting price movements using technical indicators: Investigating the impact of varying input window length. Neurocomputing 264, pp. 71--88. (10.1016/j.neucom.2016.11.095)
• Zhai, J., Cao, Y., Yao, Y., Ding, X. and Li, Y. 2017. Coarse and fine identification of collusive clique in financial market. Expert Systems with Applications 69, pp. 225-238. (10.1016/j.eswa.2016.10.051)
• Zhai, J., Cao, Y., Yao, Y., Ding, X. and Li, Y. 2017. Computational intelligent hybrid model for detecting disruptive trading activity. Decision Support Systems 93, pp. 26--41. (10.1016/j.dss.2016.09.003)

2016

• Cao, Y., Li, Y., Coleman, S., Belatreche, A. and McGinnity, T. M. 2016. Detecting wash trade in financial market using digraphs and dynamic programming. IEEE Transactions on Neural Networks and Learning Systems 27(11), pp. 2351-2363. (10.1109/TNNLS.2015.2480959)
• Raza, H., Cecotti, H., Li, Y. and Prasad, G. 2016. Adaptive learning with covariate shift-detection for motor imagery-based brain–computer interface. Soft Computing 20(8), pp. 3085--3096. (10.1007/s00500-015-1937-5)
• Liu, J., Harkin, J., Li, Y. and Maguire, L. P. 2016. Fault-tolerant networks-on-chip routing with coarse and fine-grained look-ahead. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 35(2), pp. 260-273. (10.1109/TCAD.2015.2459050)

2015

• Liu, J., Harkin, J., Li, Y. and Maguire, L. 2015. Low cost fault-tolerant routing algorithm for Networks-on-Chip. Microprocessors and Microsystems 39(6), pp. 358-372. (10.1016/j.micpro.2015.06.002)
• Ding, X., Li, Y., Belatreche, A. and Maguire, L. P. 2015. Novelty detection using level set methods. IEEE Transactions on Neural Networks and Learning Systems 26(3), pp. 576-588. (10.1109/TNNLS.2014.2320293)
• Raza, H., Prasad, G. and Li, Y. 2015. EWMA model based shift-detection methods for detecting covariate shifts in non-stationary environments. Pattern Recognition 48(3), pp. 659-669. (10.1016/j.patcog.2014.07.028)
• Cao, Y., Li, Y., Coleman, S., Belatreche, A. and McGinnity, T. M. 2015. Adaptive hidden Markov model with anomaly states for price manipulation detection. IEEE Transactions on Neural Networks and Learning Systems 26(2), pp. 318-330. (10.1109/TNNLS.2014.2315042)
• Taherkhani, A., Belatreche, A., Li, Y. and Maguire, L. P. 2015. DL-ReSuMe: A delay learning-based remote supervised method for spiking neurons. IEEE Transactions on Neural Networks and Learning Systems 26(12), pp. 3137-3149. (10.1109/TNNLS.2015.2404938)

2014

• Liu, J., Harkin, J., Li, Y., Maguire, L. and Linares-Barranco, A. 2014. Low overhead monitor mechanism for fault-tolerant analysis of NoC. Presented at: 8th International Symposium On Embedded Multicore/manycore Socs, Aizu-Wakamatsu, Japan, 23-25 Sep 20148th International Symposium on Embedded Multicore/manycore Socs. IEEE pp. 189-196., (10.1109/MCSoC.2014.35)
• Liu, J., Harkin, J., Li, Y. and Maguire, L. 2014. Online fault detection for Networks-on-Chip interconnect. Presented at: 2014 NASA/ESA Conference on Adaptive Hardware and Systems (AHS), Leicester, UK, 14-17 Jul 20142014 NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2014). Piscataway, NJ: IEEE pp. 31-38., (10.1109/AHS.2014.6880155)
• Ding, X., Li, Y., Belatreche, A. and Maguire, L. P. 2014. An experimental evaluation of novelty detection methods. Neurocomputing 135, pp. 313-327. (10.1016/j.neucom.2013.12.002)
• Cao, Y., Li, Y., Coleman, S., Belatreche, A. and McGinnity, T. M. 2014. A hidden Markov model with abnormal states for detecting stock price manipulation. Presented at: SMC 2013, Manchester, UK, 13-16 Oct 20132013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics Piscataway, NJ: IEEE pp. 3014-3019., (10.1109/SMC.2013.514)
• Raza, H., Prasad, G. and Li, Y. 2014. Dataset shift detection in non-stationary environments using EWMA charts. Presented at: 2013 IEEE International Conference on Systems, Man, and Cybernetics, Manchester, UK, 13-16 Oct 20132013 IEEE International Conference on Systems, Man, and Cybernetics. Piscataway, New Jersey: IEEE pp. 3151-3156., (10.1109/SMC.2013.537)
• Ding, X., Li, Y., Belatreche, A. and Maguire, L. P. 2014. Novelty detection using level set methods with adaptive boundaries. Presented at: SMC 2013, Manchester, UK, 13-16 Oct 20132013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics Piscataway, NJ: IEEE pp. 3020-3025., (10.1109/SMC.2013.515)
• Liu, J., Harkin, J., Li, Y. and Maguire, L. 2014. Online traffic-aware fault detection for networks-on-chip. Journal of Parallel and Distributed Computing 74(1), pp. 1984-1993. (10.1016/j.jpdc.2013.09.001)
• McDonald, S., Coleman, S., McGinnity, T. M. and Li, Y. 2014. A hybrid forecasting approach using ARIMA models and self-organising fuzzy neural networks for capital markets. Presented at: 2013 International Joint Conference on Neural Networks (IJCNN), Dallas, TX. USA, 4-9 August 2013The 2013 International Joint Conference on Neural Networks (IJCNN). IEEE pp. 1-7., (10.1109/IJCNN.2013.6706965)

2013

• Raza, H., Prasad, G. and Li, Y. 2013. EWMA based two-stage dataset shift-detection in non-stationary environments. Presented at: AIAI 2013, Paphos, Cyprus, 30 Sep - 2 Oct 2013 Presented at Papadopoulos, H. et al. eds.Artificial Intelligence Applications and Innovations, Vol. 412. IFIP Advances in Information and Communication Technology Berlin, Heidelberg: Springer pp. 625-635., (10.1007/978-3-642-41142-7_63)
• Goel, G., Maguire, L., Li, Y. and McLoone, S. 2013. Evaluation of sampling methods for learning from imbalanced data. Presented at: ICIC 2013, Nanning, China, 28-31 Jul 2013 Presented at Huang, D. et al. eds.Intelligent Computing Theories, Vol. 7995. Information Systems and Applications, incl. Internet/Web, and HCI Berlin, Heidelberg: Springer pp. 392-401., (10.1007/978-3-642-39479-9_47)

2012

• Ding, X., Li, Y., Belatreche, A. and Maguire, L. 2012. Constructing minimum volume surfaces using level set methods for novelty detection. Presented at: IJCNN 2012 International Join Conference on Neural Networks, Brisbane, QLD, Australia, 10-15 June 2012The 2012 International Joint Conference on Neural Networks (IJCNN). IEEE International Joint Conference on Neural Networks (IJCNN) IEEE pp. 1-6., (10.1109/IJCNN.2012.6252804)

2011

• Zhang, K., Li, Y., Scarf, P. and Ball, A. 2011. Feature selection for high-dimensional machinery fault diagnosis data using multiple models and Radial Basis Function networks. Neurocomputing 74(17), pp. 2941-2952. (10.1016/j.neucom.2011.03.043)
• Zhang, K., Ball, A. D., Li, Y. and Gu, F. 2011. A novel feature selection algorithm for high-dimensional condition monitoring data. International Journal of Condition Monitoring 1(1), pp. 33-43. (10.1784/204764211798089075)
• Li, Y. and Maguire, L. 2011. Selecting critical patterns based on local geometrical and statistical information. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(6), pp. 1189-1201. (10.1109/TPAMI.2010.188)
• Li, Y. 2011. Selecting training points for one-class support vector machines. Pattern recognition letters 32(11), pp. 1517-1522. (10.1016/j.patrec.2011.04.013)

2009

• Li, Y. 2009. A surface representation approach for novelty detection. Presented at: International Conference on Information and Automation 2008, Changsha, China, 20-23 June 20082008 International Conference on Information and Automation. IEEE pp. 1464-1468., (10.1109/ICINFA.2008.4608233)

2007

• Zhang, K., Ball, A., Gu, F. and Li, Y. 2007. A hybrid model with a weighted voting scheme for feature selection in machinery condition monitoring. Presented at: IEEE International Conference on Automation Science and Engineering 2007, Scottsdale, AZ, United States, 22-25 September 20072007 IEEE International Conference on Automation Science and Engineering. IEEE pp. 174-179., (10.1109/COASE.2007.4341697)

2006

• Ben Sasi, A. Y., Gu, F., Li, Y. and Ball, A. D. 2006. A validated model for the prediction of rotor bar failure in squirrel-cage motors using instantaneous angular speed. Mechanical Systems and Signal Processing 20(7), pp. 1572-1589. (10.1016/j.ymssp.2005.09.010)
• Li, Y., McLean, D., Bandar, Z., O'Shea, J. and Crockett, K. 2006. Sentence similarity based on semantic nets and corpus statistics. IEEE Transactions on Knowledge and Data Engineering 18(8), pp. 1138-1150. (10.1109/TKDE.2006.130)

2005

• Li, Y., Gu, F., Harris, G., Ball, A., Bennett, N. and Travis, K. 2005. The measurement of instantaneous angular speed. Mechanical Systems and Signal Processing 19(4), pp. 786-805. (10.1016/j.ymssp.2004.04.003)
• Gu, F., Yesilyurt, I., Li, Y., Harris, G. and Ball, A. 2005. An investigation of the effects of measurement noise in the use of instantaneous angular speed for machine diagnosis. Mechanical Systems and Signal Processing 20(6), pp. 1444-1460. (10.1016/j.ymssp.2005.02.001)

2003

• Li, Y., Bandar, Z. and McLean, D. 2003. An approach for measuring semantic similarity between words using multiple information sources. IEEE Transactions on Knowledge and Data Engineering 15(4), pp. 871-882. (10.1109/TKDE.2003.1209005)

2002

• Li, Y., Bandar, Z. and Mclean, D. 2002. Measuring semantic similarity between words using lexical knowledge and neural networks. Presented at: 3rd International Conference on Intelligent Data Engineering and Automated Learning — IDEAL 2002, Manchester, England, UK, 12-14 August 2002Intelligent Data Engineering and Automated Learning — IDEAL 2002, Vol. 2412. Lecture Notes in Computer Science Berlin and Heidelberg: Springer pp. 111-116., (10.1007/3-540-45675-9_19)
• Li, Y., Pont, M. J. and Jones, N. B. 2002. Improving the performance of radial basis function classifiers in condition monitoring and fault diagnosis applications where 'unknown' faults may occur. Pattern Recognition Letters 23(5), pp. 569-577. (10.1016/S0167-8655(01)00133-7)
• Li, Y., Pont, M. J. and Barrie Jones, N. 2002. Improving the performance of radial basis function classifiers in condition monitoring and fault diagnosis applications where `unknown' faults may occur. Pattern recognition letters 23(5), pp. 569-577. (10.1016/S0167-8655(01)00133-7)

2001

• Li, Y., Pont, M. J., Jones, N. B. and Twiddle, J. 2001. Applying MLP and RBF classifiers in embedded condition monitoring and fault diagnosis systems. Transactions of the Institute of Measurement and Control 23(5), pp. 315-343. (10.1177/014233120102300504)

2000

• Li, Y., Pont, M. J., Parikh, C. R. and Jones, N. B. 2000. Comparing the performance of three neural classifiers for use in embedded applications. Presented at: Workshop 99 on Recent Advances in Soft Computing, Leicester, England, 01-02 July 1999 Presented at John, R. and Birkenhead, R. eds.Soft Computing Techniques and Applications. Advances in Soft Computing Physica pp. 34-29.