65 research outputs found
Optimized Projection for Hashing
Hashing, which seeks for binary codes to represent data, has drawn increasing research interest in recent years. Most existing Hashing methods follow a projection-quantization framework which first projects high-dimensional data into compact low-dimensional space and then quantifies the compact data into binary codes. The projection step plays a key role in Hashing and academia has paid considerable attention to it. Previous works have proven that a good projection should simultaneously 1) preserve important information in original data, and 2) lead to compact representation with low quantization error. However, they adopted a greedy two-step strategy to consider the above two properties separately. In this paper, we empirically show that such a two-step strategy will result in a sub-optimal solution because the optimal solution to 1) limits the feasible set for the solution to 2). We put forward a novel projection learning method for Hashing, dubbed Optimized Projection (OPH). Specifically, we propose to learn the projection in a unified formulation which can find a good trade-off such that the overall performance can be optimized. A general framework is given such that OPH can be incorporated with different Hashing methods for different situations. We also introduce an effective gradient-based optimization algorithm for OPH. We carried out extensive experiments for Hashing-based Approximate Nearest Neighbor search and Content-based Data Retrieval on six benchmark datasets. The results show that OPH significantly outperforms several state-of-the-art related Hashing methods
Assessment of anxiety and depression among dental practitioners in a dental school in South Kerala
A fast synthesis of near-infrared emitting CdTe/CdSe quantum dots with small hydrodynamic diameter for in vivo imaging probes
Hyperbranched fluorocopolymers by atom transfer radical self-condensing vinyl copolymerization
Urocortin 3 expression at baseline and during inflammation in the colon: Corticotropin releasing factor receptors cross-talk
Urocortins (Ucn1–3), members of the corticotropin-releasing factor (CRF) family of neuropeptides, are emerging as potent immunomodulators. Localized, cellular expression of Ucn1 and Ucn2, but not Ucn3, has been demonstrated during inflammation. Here, we investigated the role of Ucn3 in a rat model of Crohn’s colitis and the relative contribution of CRF receptors (CRF(1) and CRF(2)) in regulating Ucn3 expression at baseline and during inflammation. Ucn3 mRNA and peptide were ubiquitously expressed throughout the GI tract in naïve rats. Ucn3 immunoreactivity was seen in epithelial cells and myenteric neurons. On day 1 of colitis, Ucn3 mRNA levels decreased by 80% and did not recover to baseline even by day 9. Next, we ascertained pro- or anti-inflammatory actions of Ucn3 during colitis. Surprisingly, unlike observed anti-inflammatory actions of Ucn1, exogenous Ucn3 did not alter histopathological outcomes during colitis and neither did it alter levels of pro-inflammatory cytokines IL-6 and TNF-α. At baseline, colon-specific knockdown of CRF(1), but not CRF(2) decreased Ucn3 mRNA by 78%, whereas during colitis, Ucn3 mRNA levels increased after CRF(1) knockdown. In cultured cells, co-expression of CRF(1) + CRF(2) attenuated Ucn3-stimulated intracellular Ca(2+) peak by 48% as compared to cells expressing CRF(2) alone. Phosphorylation of p38 kinase increased by 250% during colitis and was significantly attenuated after Ucn3 administration. Thus, our results suggest that a balanced and coordinated expression of CRF receptors is required for proper regulation of Ucn3 at baseline and during inflammation
Grafting of water-soluble phosphines to dendrimers and their use in catalysis: positive dendritic effects in aqueous media
An investigation on the correlation between the mechanical property change and the alterations in composition and microstructure of a porcine vascular tissue underwent trypsin-based decellularization treatment
Disparity estimation in stereo video sequence with adaptive spatiotemporally consistent constraints
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