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Bibliographic details on A Novel Local Features Based Salient Object Recognition Algorithm via Hybrid SVM-QPSO Model.
This paper forms saliency detection as a mathematical programming problem with which to learn a nonlinear feature mapping from multi-view features to ...
Afterwards, the SIFT features clustering and local features matching process can be implemented through the proposed hybrid SVM-QPSO model. To promote the ...
A Novel Local Features Based Salient Object Recognition Algorithm via Hybrid SVM-QPSO Model · Xin WangT. ZhaoYi Zeng. Computer Science. J. Multim. 2014. TLDR.
Afterwards, the SIFT features clustering and local features matching process can be implemented through the proposed hybrid SVM-QPSO model. To promote the ...
This paper focuses on the detection of salient objects, especially in low-contrast images. To this end, a hybrid deep-learning architecture is proposed.
Missing: Algorithm QPSO
The proposed method consists of the following four steps: (1) regional feature extraction; (2) background and foreground dictionaries extraction according to ...
In this paper, different from existing approaches, we propose a novel regularization model for the salient object detection, which integrates a weighted group ...
Missing: SVM- | Show results with:SVM-
An overview of the many methods used for fault detection, classification and location in the power system, particularly in transmission lines, ...
In this repository, we mainly focus on deep learning based saliency methods (2D RGB, 3D RGB-D/T, Video SOD and 4D Light Field) and provide a summary (Code ...