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ECCV
2008
Springer
16 years 6 months ago
Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
PDP
2010
IEEE
15 years 11 months ago
Trusted Interaction Patterns in Large-scale Enterprise Service Networks
Abstract—The evolution towards cross-organizational collaboration and interaction patterns has led to the emergence of scalable, Web services-based composition infrastructures. T...
Florian Skopik, Daniel Schall, Schahram Dustdar
3DOR
2010
14 years 12 months ago
Learning the Compositional Structure of Man-Made Objects for 3D Shape Retrieval
While approaches based on local features play a more and more important role for 3D shape retrieval, the problems of feature selection and similarity measurement between sets of l...
Raoul Wessel, Reinhard Klein
ACISICIS
2007
IEEE
15 years 11 months ago
A Composite Descriptor for Shape Retrieval
In this paper, a composite descriptor for shape retrieval has been proposed. The proposed descriptor is obtained from Generic Fourier Descriptors (GFD) for the shape region and th...
Atul Sajjanhar, Guojun Lu, Dengsheng Zhang, Wanlei...
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AIPR
2006
IEEE
15 years 11 months ago
Data Fusion, De-noising, and Filtering to Produce Cloud-Free High Quality Temporal Composites Employing Parallel Temporal Map Al
Remotely sensed images from satellite sensors such as MODIS Aqua and Terra provide high temporal resolution and wide area coverage. Unfortunately, these images frequently include ...
Bijay Shrestha, Charles G. O'Hara, Preeti Mali