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SCALESPACE
2009
Springer
15 years 11 months ago
Pre-image as Karcher Mean Using Diffusion Maps: Application to Shape and Image Denoising
In the context of shape and image modeling by manifold learning, we focus on the problem of denoising. A set of shapes or images being known through given samples, we capture its s...
Nicolas Thorstensen, Florent Ségonne, Renau...
CVPR
2011
IEEE
15 years 14 days ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell
SMC
2007
IEEE
15 years 11 months ago
Enhancing embodied evolution with punctuated anytime learning
—This paper discusses a new implementation of embodied evolution that uses the concept of punctuated anytime learning to increase the complexity of tasks that the learning system...
Gary B. Parker, Gregory E. Fedynyshyn
CVPR
2007
IEEE
16 years 7 months ago
Hierarchical Learning of Curves Application to Guidewire Localization in Fluoroscopy
In this paper we present a method for learning a curve model for detection and segmentation by closely integrating a hierarchical curve representation using generative and discrim...
Adrian Barbu, Vassilis Athitsos, Bogdan Georgescu,...
DCC
2006
IEEE
16 years 4 months ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley