Saman Halgamuge
Saman Halgamuge was educated in Germany and Sri Lanka and he is currently a Professor of University of Melbourne, Australia. He is an elected Fellow of Institute of Electrical and Electronics Engineers, USA, Institute of Engineering Technology (IET) UK and National Academy of Sciences Sri Lanka (NASSL). He is a highly cited expert in his field and listed as one of the top 2% cited experts for AI and Image Processing in the Stanford University Database published since 2020. His most-cited paper being ''Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients'', with over 4000 citations, according to GoogleScholar. He is a Distinguished Speaker/Lecturer on Computational Intelligence appointed by IEEE. He has supervised 45 PhD scholars to completion and delivered over 60 keynotes at International and national conferences. Provided by Wikipedia
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Minimum-Cost Heterogeneous Node Placement in Wireless Sensor Networks by Yahui Sun, Saman Halgamuge
Published 2019-01-01
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The node-weighted Steiner tree approach to identify elements of cancer-related signaling pathways by Yahui Sun, Chenkai Ma, Saman Halgamuge
Published 2017-12-01
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IMPARO: inferring microbial interactions through parameter optimisation by Rajith Vidanaarachchi, Marnie Shaw, Sen-Lin Tang, Saman Halgamuge
Published 2020-08-01
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An Extended Growing Self-Organizing Map for Selection of Clusters in Sensor Networks by Siddeswara Mayura Guru, Arthur Hsu, Saman Halgamuge, Saman Fernando
Published 2005-01-01
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Assessing Species Diversity Using Metavirome Data: Methods and Challenges by Damayanthi Herath, Duleepa Jayasundara, David Ackland, Isaam Saeed, Sen-Lin Tang, Saman Halgamuge
Published 2017-01-01
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Annotation-efficient deep learning for breast cancer whole-slide image classification using tumour infiltrating lymphocytes and slide-level labels by Rashindrie Perera, Peter Savas, Damith Senanayake, Roberto Salgado, Heikki Joensuu, Sandra O’Toole, Jason Li, Sherene Loi, Saman Halgamuge
Published 2024-07-01
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Visualization of incrementally learned projection trajectories for longitudinal data by Tamasha Malepathirana, Damith Senanayake, Vini Gautam, Martin Engel, Rachelle Balez, Michael D. Lovelace, Gayathri Sundaram, Benjamin Heng, Sharron Chow, Christopher Marquis, Gilles J. Guillemin, Bruce Brew, Chennupati Jagadish, Lezanne Ooi, Saman Halgamuge
Published 2024-06-01
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