2021
Akbari, B., Thiyagalingam, J., Lee, R., & Thia, K. (2021). A Multilane Tracking Algorithm Using IPDA with Intensity Feature. SENSORS, 21(2). doi:10.3390/s21020461DOI: 10.3390/s21020461
2020
Zhang, L., Thiyagalingam, J., Xue, A., & Xu, S. (2020). A Novel Method for Sea-Land Clutter Separation Using Regularized Randomized and Kernel Ridge Neural Networks. SENSORS, 20(22). doi:10.3390/s20226491DOI: 10.3390/s20226491
2019
Siso, S., Armour, W., & Thiyagalingam, J. (2019). Evaluating Auto-Vectorizing Compilers through Objective Withdrawal of Useful Information. ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION, 16(4). doi:10.1145/3356842DOI: 10.1145/3356842
2018
Xie, Y., Xiao, J., Huang, K., Thiyagalingam, J., & Zhao, Y. (2018). Correlation Filter Selection for Visual Tracking Using Reinforcement Learning. IEEE Transactions on Circuits and Systems for Video Technology, 30(1), 192-204. doi:10.1109/tcsvt.2018.2889488DOI: 10.1109/tcsvt.2018.2889488
Yang, B., Wang, J., Yuan, C., Thiyagalingam, J., & Kirubarajan, T. (2018). Multi-object Bayesian filters with amplitude information in clutter background. SIGNAL PROCESSING, 152, 22-34. doi:10.1016/j.sigpro.2018.05.004DOI: 10.1016/j.sigpro.2018.05.004
Zhou, H., Huang, J., Lu, F., Thiyagalingam, J., & Kirubarajan, T. (2018). Echo state kernel recursive least squares algorithm for machine condition prediction. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 111, 68-86. doi:10.1016/j.ymssp.2018.03.047DOI: 10.1016/j.ymssp.2018.03.047
Zhang, S., Thiyagalingam, J., Sheng, W., Kirubarajan, T., & Ma, X. (2018). Low-complexity adaptive broadband beamforming based on the non-uniform decomposition method. SIGNAL PROCESSING, 151, 66-75. doi:10.1016/j.sigpro.2018.05.003DOI: 10.1016/j.sigpro.2018.05.003
Alhijaillan, H., Coenen, F., Dukes-McEwan, J., & Thiyalgalingam, J. (2018). Segmenting sound waves to support Phonocardiogram analysis: the PCGseg Approach. In Society for the study of artificial intelligence and simulation of behaviour (AISB). Liverpool.
Location-aware convolutional neural networks based breast tumor detection (Conference Paper)
Huafeng Hu., Coenen, F., Fei Ma., Thiyagalingam, J., & Jionglong Su. (2018). Location-aware convolutional neural networks based breast tumor detection. In IET Doctoral Forum on Biomedical Engineering, Healthcare, Robotics and Artificial Intelligence 2018 (BRAIN 2018). Institution of Engineering and Technology. doi:10.1049/cp.2018.1724DOI: 10.1049/cp.2018.1724
2017
Thiyagalingam, J., Kekempanos, L., & Maskell, S. (2017). MapReduce particle filtering with exact resampling and deterministic runtime. Eurasip Journal on Advances in Signal Processing, 2017, 23 pages. doi:10.1186/s13634-017-0505-9DOI: 10.1186/s13634-017-0505-9
Fast and reliable human action recognition in video sequences by sequential analysis (Conference Paper)
Fang, H., Thiyagalingam, J., Bessis, N., & Edirisinghe, E. (2017). Fast and reliable human action recognition in video sequences by sequential analysis. In 2017 IEEE International Conference on Image Processing (ICIP). IEEE. doi:10.1109/icip.2017.8297028DOI: 10.1109/icip.2017.8297028
Parallelising Particle Filters with Deterministic Runtime on Distributed Memory Systems (Conference Paper)
Varsi, A., Kekempanos, L., Thiyagalingam, J., & Maskell, S. (2017). Parallelising Particle Filters with Deterministic Runtime on Distributed Memory Systems. In IET 3rd International Conference on Intelligent Signal Processing (ISP 2017). Institution of Engineering and Technology. doi:10.1049/cp.2017.0357DOI: 10.1049/cp.2017.0357
2015
Glyph-Based Video Visualization for Semen Analysis (Journal article)
Duffy, B., Thiyagalingam, J., Walton, S., Smith, D. J., Trefethen, A., Kirkman-Brown, J. C., . . . Chen, M. (2015). Glyph-Based Video Visualization for Semen Analysis. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 21(8), 980-993. doi:10.1109/TVCG.2013.265DOI: 10.1109/TVCG.2013.265
2014
Visualizing Cardiovascular Magnetic Resonance (CMR) imagery: Challenges and opportunities (Journal article)
Walton, S., Berger, K., Thiyagalingam, J., Duffy, B., Fang, H., Holloway, C., . . . Chen, M. (2014). Visualizing Cardiovascular Magnetic Resonance (CMR) imagery: Challenges and opportunities. Progress in Biophysics and Molecular Biology, 115(2-3), 349-358. doi:10.1016/j.pbiomolbio.2014.07.009DOI: 10.1016/j.pbiomolbio.2014.07.009
Visual Multiplexing (Journal article)
Chen, M., Walton, S., Berger, K., Thiyagalingam, J., Duffy, B., Fang, H., . . . Trefethen, A. E. (2014). Visual Multiplexing. COMPUTER GRAPHICS FORUM, 33(3), 241-250. doi:10.1111/cgf.12380DOI: 10.1111/cgf.12380
2013
Energy-aware software: Challenges, opportunities and strategies (Journal article)
Trefethen, A. E., & Thiyagalingam, J. (2013). Energy-aware software: Challenges, opportunities and strategies. JOURNAL OF COMPUTATIONAL SCIENCE, 4(6), 444-449. doi:10.1016/j.jocs.2013.01.005DOI: 10.1016/j.jocs.2013.01.005
Design and initial performance of a high-level unstructured mesh framework on heterogeneous parallel systems (Journal article)
Mudalige, G. R., Giles, M. B., Thiyagalingam, J., Reguly, I. Z., Bertolli, C., Kelly, P. H. J., & Trefethen, A. E. (2013). Design and initial performance of a high-level unstructured mesh framework on heterogeneous parallel systems. PARALLEL COMPUTING, 39(11), 669-692. doi:10.1016/j.parco.2013.09.004DOI: 10.1016/j.parco.2013.09.004
The Effect of Topology-Aware Process and Thread Placement on Performance and Energy (Conference Paper)
Solernou, A., Thiyagalingam, J., Duta, M. C., & Trefethen, A. E. (2013). The Effect of Topology-Aware Process and Thread Placement on Performance and Energy. In SUPERCOMPUTING (ISC 2013) Vol. 7905 (pp. 357-371). Retrieved from https://www.webofscience.com/
Complexity Plots (Journal article)
Thiyagalingam, J., Walton, S., Duffy, B., Trefethen, A., & Chen, M. (2013). Complexity Plots. COMPUTER GRAPHICS FORUM, 32(3), 111-120. doi:10.1111/cgf.12098DOI: 10.1111/cgf.12098
2011
Thiyagalingam, J., Goodman, D., Schnabel, J. A., Trefethen, A., & Grau, V. (2011). On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences.. International journal of biomedical imaging, 2011, 137604. doi:10.1155/2011/137604DOI: 10.1155/2011/137604
Breaking the GPU programming barrier with the auto-parallelising SAC compiler (Conference Paper)
Guo, J., Thiyagalingam, J., & Scholz, S. -B. (2011). Breaking the GPU programming barrier with the auto-parallelising SAC compiler. In Proceedings of the sixth workshop on Declarative aspects of multicore programming. ACM. doi:10.1145/1926354.1926359DOI: 10.1145/1926354.1926359
2010
Parallel Simulation for Parameter Estimation of Optical Tissue Properties (Conference Paper)
Duta, M., Thiyagalingam, J., Trefethen, A., Goyal, A., Grau, V., & Smith, N. (2010). Parallel Simulation for Parameter Estimation of Optical Tissue Properties. In EURO-PAR 2010 - PARALLEL PROCESSING, PART II Vol. 6272 (pp. 51-+). Retrieved from https://www.webofscience.com/
Towards compiling SAC to CUDA (Chapter)
Guo, J., Thiyagalingam, J., & Scholz, S. B. (2010). Towards compiling SAC to CUDA. In Trends in Functional Programming 10 (pp. 33-48).
2008
Component-based development environment for Grid systems: Design and implementation (Conference Paper)
Basukoski, A., Getov, V., Thiyagalingam, J., & Isaiadis, S. (2008). Component-based development environment for Grid systems: Design and implementation. In MAKING GRIDS WORK (pp. 119-128). doi:10.1007/978-0-387-78448-9_9DOI: 10.1007/978-0-387-78448-9_9
Advanced Grid Programming with Components: A Biometric Identification Case Study (Conference Paper)
Weigold, T., Buhler, P., Thiyagalingam, J., Basukoski, A., & Getov, V. (2008). Advanced Grid Programming with Components: A Biometric Identification Case Study. In 2008 32nd Annual IEEE International Computer Software and Applications Conference. IEEE. doi:10.1109/compsac.2008.97DOI: 10.1109/compsac.2008.97
2006
A metadata extracting tool for software components in grid applications (Conference Paper)
Thiyagalingam, J., & Getov, V. (2006). A metadata extracting tool for software components in grid applications. In Proceedings - IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing, JVA 2006 (pp. 189-196). doi:10.1109/JVA.2006.3lDOI: 10.1109/JVA.2006.3l
A metadata extracting tool for software components in grid applications (Conference Paper)
Thiyagalingam, J., & Getov, V. (2006). A metadata extracting tool for software components in grid applications. In IEEE JOHN VINCENT ATANASOFF 2006 INTERNATIONAL SYMPOSIUM ON MODERN COMPUTING, PROCEEDINGS (pp. 189-+). doi:10.1109/JVA.2006.3DOI: 10.1109/JVA.2006.3
Minimizing associativity conflicts in Morton layout (Conference Paper)
Thiyagalingam, J., Beckmann, O., & Kelly, P. H. J. (2006). Minimizing associativity conflicts in Morton layout. In PARALLEL PROCESSING AND APPLIED MATHEMATICS Vol. 3911 (pp. 1082-1088). Retrieved from https://www.webofscience.com/
Is Morton layout competitive for large two-dimensional arrays yet? (Conference Paper)
Thiyagalingam, J., Beckmann, O., & Kelly, P. H. J. (2006). Is Morton layout competitive for large two-dimensional arrays yet?. In CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE Vol. 18 (pp. 1509-1539). doi:10.1002/cpe.1018DOI: 10.1002/cpe.1018
2004
Improving the performance of morton layout by array alignment and loop unrolling - Reducing the price of naivety (Journal article)
Thiyagalingam, J., Beckmann, O., & Kelly, P. H. J. (2004). Improving the performance of morton layout by array alignment and loop unrolling - Reducing the price of naivety. LANGUAGES AND COMPILERS FOR PARALLEL COMPUTING, 2958, 241-257. doi:10.1007/978-3-540-24644-2_16DOI: 10.1007/978-3-540-24644-2_16
2002
Is morton layout competitive for large two-dimensional arrays? (Conference Paper)
Thiyagalingam, J., & Kelly, P. H. J. (2002). Is morton layout competitive for large two-dimensional arrays?. In EURO-PAR 2002 PARALLEL PROCESSING, PROCEEDINGS Vol. 2400 (pp. 280-288). Retrieved from https://www.webofscience.com/