6 search results - page 1 / 2 » Safety in Numbers: Learning Categories from Few Examples wit... |
CVPR
2010
IEEE
14 years 1 months ago
2010
IEEE
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...
Publication
In this paper, we address the problem of automatically detecting and tracking a variable number of persons in complex
scenes using a monocular, potentially moving, uncalibrated ca...
CIKM
2008
Springer
13 years 7 months ago
2008
Springer
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
ICDM
2008
IEEE
13 years 11 months ago
2008
IEEE
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...