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Unsupervised image hashing has recently gained significant momentum due to the scarcity of reliable supervision knowledge, such as class labels and pairwise relationship. Previous unsupervised methods heavily rely on constructing sufficiently large affinity matrix for exploring the geometric structure of data. Nevertheless, due to lack of adequately preserving the intrinsic information of original visual data, satisfactory performance can hardly be achieved. In this article, we propose a novel approach, called bidirectional discrete matrix factorization hashing (BDMFH), which alternates two mutually promoted processes of 1) learning binary codes from data and 2) recovering data from the binary codes. In particular, we design the inverse factorization model, which enforces the learned binary codes inheriting intrinsic structure from the original visual data. Moreover, we develop an efficient discrete optimization algorithm for the proposed BDMFH. Comprehensive experimental results on three large-scale benchmark datasets show that the proposed BDMFH not only significantly outperforms the state-of-the-arts but also provides the satisfactory computational efficiency.
This article was published in the following journal.
Name: IEEE transactions on cybernetics
For large-scale image retrieval task, a hashing technique has attracted extensive attention due to its efficient computing and applying. By using the hashing technique in image retrieval, it is crucia...
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Compact hash code learning has been widely applied to fast similarity search owing to its significantly reduced storage and highly efficient query speed. However, it is still a challenging task to lea...
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A method of delineating blood vessels by subtracting a tissue background image from an image of tissue plus intravascular contrast material that attenuates the X-ray photons. The background image is determined from a digitized image taken a few moments before injection of the contrast material. The resulting angiogram is a high-contrast image of the vessel. This subtraction technique allows extraction of a high-intensity signal from the superimposed background information. The image is thus the result of the differential absorption of X-rays by different tissues.
A secreted matrix metalloproteinase that is the predominant proteolytic activity in the enamel matrix. The enzyme has a high specificity for dental enamel matrix protein AMELOGENIN.
A transmembrane domain-containing matrix metalloproteinase. It is synthesized as an inactive zymogen that is activated by the proteolytic action of PROPROTEIN CONVERTASES. Matrix metalloproteinase 16 plays a direct role in the cleavage of proteins in the pericellular environment. In addition it can function indirectly by enzymatically activating the proprotein form of other MATRIX METALLOPROTEINASES such as the zymogen of MATRIX METALLOPROTEINASE 2.
A secreted matrix metalloproteinase that is believed to play a role in EXTRACELLULAR MATRIX remodeling and cell fate determination during normal and pathological processes. Matrix metalloproteinase 11 was originally isolated in primary BREAST NEOPLASMS and may be involved in the process of tumorigenesis.
The production of an image obtained by cameras that detect the radioactive emissions of an injected radionuclide as it has distributed differentially throughout tissues in the body. The image obtained from a moving detector is called a scan, while the image obtained from a stationary camera device is called a scintiphotograph.