Similarity metrics that are learned from labeled training
data can be advantageous in terms of performance
and/or efficiency. These learned metrics can then be used
in conjuncti...
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Much past research on finding text in natural scenes uses bottom-up grouping processes to detect candidate text features as a first processing step. While such grouping procedures...
In this paper, we present a flexible accelerator designed for networking applications. The accelerator can be utilized efficiently by a variety of Network Processor designs. Most ...
Naive Bayes and logistic regression perform well in different regimes. While the former is a very simple generative model which is efficient to train and performs well empirically...