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ALT
1998
Springer
14 years 2 months ago
Predictive Learning Models for Concept Drift
Concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. Except for this minimum permanence, the con...
John Case, Sanjay Jain, Susanne Kaufmann, Arun Sha...
SMI
2008
IEEE
255views Image Analysis» more  SMI 2008»
14 years 4 months ago
GPU-accelerated surface denoising and morphing with lattice Boltzmann scheme
In this paper, we introduce a parallel numerical scheme, the lattice Boltzmann method, to shape modeling applications. The motivation of using this originally-designed fluid dyna...
Ye Zhao
CVPR
2005
IEEE
15 years 7 days ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman
IJCNN
2007
IEEE
14 years 4 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
ICCV
2011
IEEE
12 years 10 months ago
Learning Spatiotemporal Graphs of Human Activities
Complex human activities occurring in videos can be defined in terms of temporal configurations of primitive actions. Prior work typically hand-picks the primitives, their total...
William Brendel, Sinisa Todorovic