Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
We describe an algorithm for similar-image search which
is designed to be efficient for extremely large collections of
images. For each query, a small response set is selected by...
Lorenzo Torresani (Dartmouth College), Martin Szum...
We present an object recognition algorithm that uses model and image line features to locate complex objects in high clutter environments. Finding correspondences between model an...
Background: Identification of gene and protein names in biomedical text is a challenging task as the corresponding nomenclature has evolved over time. This has led to multiple syn...
Daniel Hanisch, Katrin Fundel, Heinz-Theodor Mevis...
Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...