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PAMI
2007
123views more  PAMI 2007»
15 years 1 months ago
Unsupervised Statistical Segmentation of Nonstationary Images Using Triplet Markov Fields
—Recent developments in statistical theory and associated computational techniques have opened new avenues for image modeling as well as for image segmentation techniques. Thus, ...
Dalila Benboudjema, Wojciech Pieczynski
199
Voted
FASE
2011
Springer
14 years 6 months ago
Automated Learning of Probabilistic Assumptions for Compositional Reasoning
Probabilistic verification techniques have been applied to the formal modelling and analysis of a wide range of systems, from communication protocols such as Bluetooth, to nanosca...
Lu Feng, Marta Z. Kwiatkowska, David Parker
FTCGV
2011
122views more  FTCGV 2011»
14 years 6 months ago
Structured Learning and Prediction in Computer Vision
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
Sebastian Nowozin, Christoph H. Lampert
129
Voted
CVPR
2007
IEEE
16 years 4 months ago
Nonnegative Tucker Decomposition
Nonnegative tensor factorization (NTF) is a recent multiway (multilinear) extension of nonnegative matrix factorization (NMF), where nonnegativity constraints are imposed on the C...
Yong-Deok Kim, Seungjin Choi
ICCV
2005
IEEE
16 years 4 months ago
Learning Non-Negative Sparse Image Codes by Convex Programming
Example-based learning of codes that statistically encode general image classes is of vital importance for computational vision. Recently, non-negative matrix factorization (NMF) ...
Christoph Schnörr, Matthias Heiler