The image data are obtained by a variety of multimedia, information equipment, which include amount of information, extensive coverage, and redundancy in ubiquitous computing paradigm. In order to make use of these in...
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Botnet is one of the major security threats to Internet. In this paper, botnet communication and attack patterns were introduced, and the discovery method of botnet based on abnormal behavior was studied. For the curr...
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Spike sorting is the essential step in analyzing recording spike signals for studying information processing mechanisms within the nervous system. Overlapping is one of the serious problems in the spike sorting of mul...
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To improve the convergence time of Ant Colony Algorithm, avoid falling in local best and enhance the quality of solution, a novel dynamic parameters ant colony algorithm with particle swarm characteristics is proposed...
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A new kind of neural-based market prediction computing approach for electronic commerce has beenpresented by our research group in this paper. Our purpose is to suggest a successful and efficient prediction method of ...
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To make predictions on unseen classes, few-shot segmentation becomes a research focus recently. However, most methods build on pixel-level annotation requiring quantity of manual work. Moreover, inherent information o...
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Spike sorting is the essential step in analyzing recording spike signals for studying information processing mechanisms within the nervous system. Overlapping is one of the most serious problems in the spike sorting f...
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With the fast development of 3D imaginations becomes more and more fascination, multi-view stereo based 3D reconstruction is a significant technique for those application. To facilitate the subsequent processing of 3D...
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A fuzzy clustering is one of important and valid methods to knowledge discovery. One of problems in fuzzy clustering is to determine a certain fuzzy sample classification in given limited sample space. Another is its ...
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Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few meth...
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Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few methods explicitly consider how to preserve modality-specific *** this study,we propose a novel framework,the specificity-preserving network(SPNet),which improves SOD performance by exploring both the shared information and modality-specific ***,we use two modality-specific networks and a shared learning network to generate individual and shared saliency prediction *** effectively fuse cross-modal features in the shared learning network,we propose a cross-enhanced integration module(CIM)and propagate the fused feature to the next layer to integrate cross-level ***,to capture rich complementary multi-modal information to boost SOD performance,we use a multi-modal feature aggregation(MFA)module to integrate the modalityspecific features from each individual decoder into the shared *** using skip connections between encoder and decoder layers,hierarchical features can be fully *** experiments demonstrate that our SPNet outperforms cutting-edge approaches on six popular RGB-D SOD and three camouflaged object detection *** project is publicly available at https://***/taozh2017/SPNet.
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