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» Learning Low-Level Vision
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ICCV
2003
IEEE
16 years 4 months ago
Weighted and Robust Incremental Method for Subspace Learning
Visual learning is expected to be a continuous and robust process, which treats input images and pixels selectively. In this paper we present a method for subspace learning, which...
Danijel Skocaj, Ales Leonardis
ECCV
2008
Springer
16 years 4 months ago
Human Activity Recognition with Metric Learning
This paper proposes a metric learning based approach for human activity recognition with two main objectives: (1) reject unfamiliar activities and (2) learn with few examples. We s...
Du Tran, Alexander Sorokin
ICPR
2008
IEEE
16 years 3 months ago
A discrete-time parallel update algorithm for distributed learning
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
Christian Bauckhage, Tansu Alpcan
ICPR
2008
IEEE
16 years 3 months ago
Prototype learning with margin-based conditional log-likelihood loss
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum...
Cheng-Lin Liu, Xiaobo Jin, Xinwen Hou
ICPR
2006
IEEE
16 years 3 months ago
Machine Learning for Video Compression: Macroblock Mode Decision
Video Compression currently is dominated by engineering and fine-tuned heuristic methods. In this paper, we propose to instead apply the well-developed machinery of machine learni...
Christoph H. Lampert