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Wu, J., Sheng-hua, Z., Ma, Z., Heinen, S. J., & Jiang, J.. (2018). Foveated convolutional neural networks for video summarization. Multimedia Tools And Applications, 77(22), 29245-29267. http://doi.org/https://doi.org/10.1007/s11042-018-5953-1 (Original work published 2018)
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Yuille, A. L., & Coughlan, J.. (2000). Fundamental limits of Bayesian inference: order parameters and phase transitions for road tracking. Pattern Analysis And Machine Intelligence, Ieee Transactions On, 22, 160–173.
Yuille, A. L., & Coughlan, J.. (1999). High-Level and Generic Models for Visual Search: When does high level knowledge help?. In Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on. (Vol. 2). IEEE.
Yuille, A. L., Coughlan, J., & Zhu, S. Chun. (2000). Unified framework for performance analysis of Bayesian inference. In AeroSense 2000 (pp. 333–346). International Society for Optics and Photonics.
Yuille, A. L., Coughlan, J., & Konishi, S.. (2003). The KGBR viewpoint-lighting ambiguity. Journal Of The Optical Society Of America (Josa) A, 20(1). (Original work published 2003)
Yuille, A. L., Coughlan, J., & Konishi, S.. (2001). The KGBR viewpoint-lighting ambiguity and its resolution by generic constraints. Computer Vision, 2001. Iccv 2001. Proceedings. Eighth Ieee International Conference On, 2, 376–382.
Yuille, A. L., Coughlan, J., & Konishi, S.. (2000). The generic viewpoint constraint resolves the generalized bas relief ambiguity. Proc. Of Conference On Information Scienes And Systems (Ciss 2000), 15–17.
Yuille, A. L., Coughlan, J., & Konishi, S.. (2003). The generic viewpoint assumption and planar bias. Ieee Transactions On Pattern Analysis And Machine Intelligence, 25, 775–778.
Yuille, A. L., Coughlan, J., Zhu, S. Chun, & Wu, Y.. (2000). Order Parameters for Minimax Entropy Distributions: When does high level knowledge help?. In Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on (Vol. 1, pp. 558–565). IEEE.

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