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  • I. Bozcan, S. Kalkan, "What is (missing or wrong) in the scene? A Hybrid Deep Boltzmann Machine For Contextualized Scene Modeling", International Conference on Robotics and Automation (ICRA), submitted, 2018. ArxivWWW
  • I. Bozcan, I. Dogan, S. Kalkan, "A Learning Based Approach to Incremental Context Modeling in Robots", International Conference on Robotics and Automation (ICRA), submitted, 2018. ArxivWWW
  • I. Dogan, S. Kalkan, "A Deep Incremental Boltzmann Machine for Modeling Context in Robots", International Conference on Robotics and Automation (ICRA), submitted, 2018. ArxivWWW
  • C. Aker, S. Kalkan, "Using Deep Networks for Drone Detection", International Workshop on Small-Drone Surveillance, Detection and Counteraction Techniques organised within AVSS, 2017. Arxiv
  • M. Yaman, S. Kalkan, "Performance Evaluation of similarity measures for dense multimodal stereo vision", J. Electron. Imaging 25(3), 033013, 2016. PreprintPublisher's Website.
  • H. Celikkanat, G. Orhan, N. Pugeault, F. Guerin, E. Sahin, S. Kalkan, "Learning Context on a Humanoid Robot using Incremental Latent Dirichlet Allocation", IEEE Transactions on Cognitive and Developmental Systems, 8(1):42-59, 2016. Technical ReportPublisher's Website.
  • H. Celikkanat, G. Orhan, S. Kalkan, "A Probabilistic Concept Web in a Humanoid Robot", IEEE Transactions on Autonomous Mental Development (TAMD), (7)2:92-106, 2015. PreprintPublisher's Website
  • H. Celikkanat, E. Sahin, S. Kalkan, "Integrating Spatial Concepts into a Probabilistic Concept Web", 17th International Conference on Advanced Robotics (ICAR), IEEE, Istanbul, 2015. pdf
  • S. Kalkan, N. Dag, O. Yuruten, A. M. Borghi, E. Sahin, "Verb Concepts from Affordances", Interaction Studies Journal, 15(1):1-37, 2014. PreprintPublisher's webpage
  • O. Yuruten, E. Sahin, S. Kalkan, "The Learning of Adjectives and Nouns from Affordance and Appearance Features", Adaptive Behavior, 21(6):437-451, 2013. PreprintPublisher
  • N. Krueger, P. Janssen, S. Kalkan, M. Lappe, A. Leonardis, J. Piater, A. J. Rodriguez-Sanchez, L. Wiskott, "Deep Hierarchies in the Primate Visual Cortex: What Can We Learn For Computer Vision?", IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 35(8):1847-1871, August 2013. Preprint
  • E. Ugur, E. Oztop, E. Sahin (2009). Affordance learning from range data for multi-step planning. Proc. of the Ninth Intl. Conf. on Epigenetic Robotics (Epirob'09), Lund University Cognitive Science Studies, 146, pp. 177-184.Earlier version also available as: pdf.
  • Sahin E., Cakmak M., Dogar M.R., Ugur E. and Ucoluk G. (2007) .To afford or not to afford: A new formalization of affordances towards affordance-based robot control. Adaptive Behavior, Vol. 15, No. 4, 447-472. Early version available as METU-CENG-TR-2006-02 in pdf. Also available as web page
  • Dorigo M., Trianni V., Sahin E., Gross R., Labella T., Baldassarre, Nolfi S., Deneubourg J.-L., Mondada F., Floreano D., and Gambardella L. (2004). Evolving Self-Organizing Behaviors for a Swarm-Bot, Autonomous Robots. volume 17, pages 223-245.
  • Bahceci E., Soysal O., Sahin E. (2003) A Review: Pattern Formation and Adaptation in Multi-Robot Systems. Technical Report CMU-RI-TR-03-43. Carnegie Mellon Univ, Pittsburgh, PA, USA.

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