Nearest neighbor search is a problem of finding the data points from the database such that
the distances from them to the query point are the smallest. Learning to hash is one of the …

Due to its low storage cost and fast query speed, cross-modal hashing (CMH) has been
widely used for similarity search in multimedia retrieval applications. However, most existing …

The explosive growth in Big Data has attracted much attention in designing efficient indexing
and search methods recently. In many critical applications such as large-scale search and …

The blooming proliferation of aeronautics and astronautics platforms, together with the ever-
increasing remote sensing imaging sensors on these platforms, has led to the formation of …

In this paper, we propose a new deep hashing (DH) approach to learn compact binary
codes for large scale visual search. Unlike most existing binary codes learning methods …

Due to its low storage cost and fast query speed, hashing has been widely adopted for
similarity search in multimedia data. In particular, more and more attentions have been …

Similarity search (nearest neighbor search) is a problem of pursuing the data items whose
distances to a query item are the smallest from a large database. Various methods have …

In this paper, we present a new multimedia retrieval paradigm to innovate large-scale
search of heterogenous multimedia data. It is able to return results of different media types …