During the last decade, the deluge of multimedia data has impacted a wide range of
research areas, including multimedia retrieval, 3D tracking, database management, data …

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 …

Finger vein recognition has drawn increasing attention from biometrics community due to its
security and convenience. In this paper, a novel discriminative binary codes (DBC) learning …

Hashing, or learning binary embeddings of data, is frequently used in nearest neighbor
retrieval. In this paper, we develop learning to rank formulations for hashing, aimed at …

Most metric learning techniques typically focus on sample embedding learning, while
implicitly assume a homogeneous local neighborhood around each sample, based on the …

Nearest neighbor search is a fundamental problem in various domains, such as computer
vision, data mining, and machine learning. With the explosive growth of data on the Internet …

With the rapid growth of fashion-focused social networks and online shopping, intelligent
fashion recommendation is now in great needs. Recommending fashion outfits, each of …

In recent years, the rapid development of remote sensing (RS) technology has led to a
drastic increase in the availability of RS images. This calls for the need to develop new …

Recent years have witnessed the success of binary hashing techniques in approximate
nearest neighbor search. In practice, multiple hash tables are usually built using hashing to …

Hash-based nearest neighbor search has become attractive in many applications. However,
the quantization in hashing usually degenerates the discriminative power when using …