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» The Dark Side of Object Learning: Learning Objects
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MM
2003
ACM
241views Multimedia» more  MM 2003»
15 years 8 months ago
Invariance in motion analysis of videos
In this paper, we propose an approach that retrieves motion of objects from the videos based on the dynamic time warping of view invariant characteristics. The motion is represent...
Cen Rao, Mubarak Shah, Tanveer Fathima Syeda-Mahmo...
NIPS
2000
15 years 4 months ago
One Microphone Source Separation
Source separation, or computational auditory scene analysis, attempts to extract individual acoustic objects from input which contains a mixture of sounds from different sources, ...
Sam T. Roweis
EMMCVPR
2011
Springer
14 years 3 months ago
Optimization of Robust Loss Functions for Weakly-Labeled Image Taxonomies: An ImageNet Case Study
The recently proposed ImageNet dataset consists of several million images, each annotated with a single object category. However, these annotations may be imperfect, in the sense t...
Julian John McAuley, Arnau Ramisa, Tibério ...
127
Voted
ICML
2006
IEEE
16 years 4 months ago
Iterative RELIEF for feature weighting
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform s...
Yijun Sun, Jian Li
ICML
2005
IEEE
16 years 4 months ago
Predicting probability distributions for surf height using an ensemble of mixture density networks
There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution for a variable rather than simply the most lik...
Michael Carney, Padraig Cunningham, Jim Dowling, C...