Intrinsically motivated learning systems based on biologically-inspired novelty detection von Gatsoulis, Y., McGinnity, T.M.

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A qualitative approach for online activity recognition von Alomari, M, Duckworth, P, Gatsoulis, Y, Hogg, DC, Cohn, AG

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Online unsupervised cumulative learning for life-long robot operation von Gatsoulis, Y., Burbridge, C., Mcginnity, T. M.

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Unsupervised Activity Recognition using Latent Semantic Analysis on a Mobile Robot von Duckworth, P, Alomari, M, Gatsoulis, Y, Hogg, DC, Cohn, AG

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Unsupervised Grounding of Textual Descriptions of Object Features and Actions in Video von Alomari, M, Chinellato, E, Gatsoulis, Y, Hogg, DC, Cohn, AG

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Biologically inspired intrinsically motivated learning for service robots based on novelty detection and habituation von Gatsoulis, Y., Burbridge, C., McGinnity, T. M.

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Primitive action learning using fuzzy neural networks von Gatsoulis, Y., Siradjuddin, I., McGinnity, T. M.

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Qualitative and quantitative spatio-temporal relations in daily living activity recognition von Tayyub, J, Tavanai, A, Gatsoulis, Y, Cohn, AG, Hogg, DC

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The STRANDS Project: Long-Term Autonomy in Everyday Environments von Hawes, N, Burbridge, C, Jovan, F, Kunze, L, Lacerda, B, Mudrová, L, Young, J, Wyatt, J, Hebesberger, D, Körtner, T, Ambrus, R, Bore, N, Folkesson, J, Jensfelt, P, Beyer, L, Hermans, A, Leibe, B, Aldoma, A, Fäulhammer, T, Zillich, M, Vincze, M, Chinellato, E, Al-Omari, M, Duckworth, P, Gatsoulis, Y, Hogg, DC, Cohn, AG, Dondrup, C, Pulido Fentanes, J, Krajník, T, Santos, JM, Duckett, T, Hanheide, M

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Imbalance of demand and supply for regionalized injury services: a case study in Greece von PETRIDOU, E., GASTOULIS, N., DESSYPRIS, N., SKALKIDIS, Y., VOROS, D., PAPADIMITRIOU, Y., TRICHOPOULOS, D.

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