In recent years a vast amount of visual content has been generated and shared from many
fields, such as social media platforms, medical imaging, and robotics. This abundance of …

With the ever increasing size of the web, relevant information extraction on the Internet with
a query formed by a few keywords has become a big challenge. Query Expansion (QE) …

The existing binary foreground map (FM) measures to address various types of errors in
either pixel-wise or structural ways. These measures consider pixel-level match or image …

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 …

Learning to hash has been widely applied to approximate nearest neighbor search for large-
scale multimedia retrieval, due to its computation efficiency and retrieval quality. Deep …

Humans inevitably develop a sense of the relationships between objects, some of which are
based on their appearance. Some pairs of objects might be seen as being alternatives to …

Benchmark datasets are critical for developing, evaluating, and comparing remote sensing
image retrieval (RSIR) approaches. However, current benchmark datasets are deficient in …

Due to its computation efficiency and retrieval quality, hashing has been widely applied to
approximate nearest neighbor search for large-scale image retrieval, while deep hashing …

In this paper, we review the background and state-of-the-art of big data. We first introduce
the general background of big data and review related technologies, such as could …

Learning effective feature representations and similarity measures are crucial to the retrieval
performance of a content-based image retrieval (CBIR) system. Despite extensive research …