With the progress of network technology, there are more and more digital images of the internet. But most images are not semantically marked, which makes it difficult to retrieve and use. In this paper, a new algorithm is proposed to automatically annotate images based on particle swarm optimization (PSO) and support vector clustering (SVC). The algorithm includes two stages: firstly, PSO algorithm is used to optimize SVC; secondly, the trained SVC algorithm is used to annotate the image automatically. In the experiment, three datasets are used to evaluate the algorithm, and the results show the effectiveness of the algorithm.
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Purpose: The MHC-unrestricted activity of cytokine-induced killer (CIK) cells against chemo-surviving melanoma cancer stem cells (mCSC) was...
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Publication date: 18 April 2017 Source: Cell Reports, Volume 19, Issue 3 Author(s): David Estoppey, Chia Min Lee, Marco Janoschke, Boon He...
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Abstract Functionalised electrospun polyamide-6 (PA-6) nanofibres incorporating gadolinium oxide nanoparticles conjugated to zinc tetracar...
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Cytokine-dependent renewal of stem cells is a fundamental requisite for tissue homeostasis and regeneration. Spermatogonial progenitor cells...
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Abstract This paper addresses the hybrid consensus-based formation keeping problem for nonholonomic mobile robots in the presence of a nov...
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Current treatments for generalized pustular psoriasis are unsatisfactory. We applied recently-developed techniques for transcriptomic analys...
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Downregulation of mouse CCR3 by lentiviral shRNA inhibits proliferation and induces apoptosis of mouse eosinophils. Mol Med Rep. 2016 ...
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