Abstract. We consider the problem of detecting a large number of different classes of objects in cluttered scenes. We present a learning procedure, based on boosted decision stumps...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
The problem of search and retrieval of images using relevance feedback has attracted tremendous attention in recent years from the research community. A real-world-deployable inte...
Pradhee Tandon, Piyush Nigam, Vikram Pudi, C. V. J...
Several applications would emerge from the development of efficient and robust sound classification systems able to identify the nature of non-speech sound sources. This paper prop...
Mauricio Kugler, Victor Alberto Parcianello Benso,...
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...