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An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

, , and . Bioinform., 19 (16): 2131-2140 (2003)

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Comparing two video-based techniques for driver fatigue detection: classification versus optical flow approach., , , , , and . Mach. Vis. Appl., 22 (4): 597-618 (2011)Semi-supervised Learning of Dynamic Self-Organising Maps., and . ICONIP (1), volume 4232 of Lecture Notes in Computer Science, page 915-924. Springer, (2006)Combining News and Technical Indicators in Daily Stock Price Trends Prediction., , and . ISNN (3), volume 4493 of Lecture Notes in Computer Science, page 1087-1096. Springer, (2007)An Extended Growing Self-Organizing Map for Selection of Clusters in Sensor Networks., , , and . IJDSN, 1 (2): 227-243 (2005)Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads., , , , , , , , and . Bioinform., 30 (8): 1064-1072 (2014)Scalable Dynamic Self-Organising Maps for Mining Massive Textual Data., , and . ICONIP (3), volume 4234 of Lecture Notes in Computer Science, page 260-267. Springer, (2006)Face Recognition by Extending Elastic Bunch Graph Matching with Particle Swarm Optimization., , and . J. Multim., 4 (4): 204-214 (2009)Binning sequences using very sparse labels within a metagenome., , , and . BMC Bioinform., (2008)Class structure visualization with semi-supervised growing self-organizing maps., and . Neurocomputing, 71 (16-18): 3124-3130 (2008)Enhancement of topology preservation and hierarchical dynamic self-organising maps for data visualisation., and . Int. J. Approx. Reason., 32 (2-3): 259-279 (2003)