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John K. Tsotsos
Home » Publications – 2013

Publications – 2013

  • Andreopoulos, A., Tsotsos, J.K., 50 Years of Object Recognition: Directions Forward, Computer Vision and Image Understanding, Vol.117, Issue 8, August 2013, p. 827-891.
  • Andreopoulos, A., & Tsotsos, J. K. (2013). A computational learning theory of active object recognition under uncertainty. International journal of computer vision, 101(1), 95-142.
  • Bruce, N.D.B., Tsotsos, J.K. “Attention in Stereo Vision: Implications for Computational Models of Attention.” (2013).
  • Pomplun, M. & Suzuki, J. Developing and Applying Biologically-Inspired Vision Systems: Interdisciplinary Concepts. IGI Global, 2013, p65-88.
  • Rodriguez-Sanchez, A.J., Dudek, G.L., Tsotsos, J.K. Curvature and Shape Processes in Vision, in Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective, ed. by S. Dickinson and Z. Pizlo, Springer, 2013, p. 429 – 442.
  • Rodríguez-Sánchez, A. J., Dudek, G.L., & Tsotsos, J. K. (2013). Detecting, Representing and Attending to Visual Shape. In Shape Perception in Human and Computer Vision (pp. 429-442). Springer London.
  • Rodriguez-Sanchez, A.J., Tsotsos, JK., The roles of endstopped and curvature tuned computations in a hierarchical representation of 2D shape, Developing and Applying Biologically‐Inspired Vision Systems: Interdisciplinary Concepts, edited by M. Pomplun and J. Suzuki, IGI Global, 2013, p184-207.
  • Rothenstein, A. L., & Tsotsos, J. K. (2013). Integrating attentional modulation with attentional selection.
  • Shi, X., Wang, B., Tsotsos, J.K., Early Recurrence Improves Edge Detection, British Machine Vision Conference, Bristol, UK, 9 – 13 Sept 2013.
  • Shi, X., Wang, B., & Tsotsos, J. K. (2013). Early recurrence improves edge detection. In Proceedings of the 24th British Machine Vision Conference.
  • Tsotsos, J. K. (2013). Cognitive programs: towards an executive controller for visual attention. In Vision Sciences Society Annual Meeting 2013.
  • Wang, B., Tu, Z., & Tsotsos, J. K. (2013, December). Dynamic label propagation for semi-supervised multi-class multi-label classification. In Computer Vision (ICCV), 2013 IEEE International Conference on (pp. 425-432). IEEE.
  • Wang, B., Tu, Z., Tsotsos, J.K., Dynamic Label Propagation for Semi-supervised Multi-class Multi-label Classification, Proc. Int. Conference on Computer Vision, Dec. 12, 2013, Sydney.
  • Wloka, C., & Tsotsos, J. (2013). Overt Fixations Reflect a Natural Central Bias. Journal of Vision, 13(9), 239-239.