Semi-supervised learning is an important and active topic of research in patternrecognition. For classification using linear discriminant analysis specifically, several semi-supervised variants have been proposed. Us...
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(纸本)9781479952106
Semi-supervised learning is an important and active topic of research in patternrecognition. For classification using linear discriminant analysis specifically, several semi-supervised variants have been proposed. Using any one of these methods is not guaranteed to outperform the supervised classifier which does not take the additional unlabeled data into account. In this work we compare traditional Expectation Maximization type approaches for semi-supervised linear discriminant analysis with approaches based on intrinsic constraints and propose a new principled approach for semi-supervised linear discriminant analysis, using so-called implicit constraints. We explore the relationships between these methods and consider the question if and in what sense we can expect improvement in performance over the supervised procedure. The constraint based approaches are more robust to misspecification of the model, and may outperform alternatives that make more assumptions on the data in terms of the log-likelihood of unseen objects.
For multi-target route optimization with constraint conditions, the mathematical model for logistics distribution route optimization is built to accelerate response speed of logistics enterprises to customers, improve...
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For multi-target route optimization with constraint conditions, the mathematical model for logistics distribution route optimization is built to accelerate response speed of logistics enterprises to customers, improve service quality, and strengthen the satisfaction of customers, and a new algorithm with the combination of genetic and ant colony algorithms is proposed to solve the selection issues of such logistics route. Initial pheromone is formed with genetic algorithm, based on which the optimal solution is rapidly sought with ant colony algorithm, and complementary advantages are achieved between above two algorithms. Application examples and simulations are available for calculation, and the results show that such algorithm is practical and effective to optimize logistics distribution route.
This paper proposes a novel method to determine the speed of the surrounding vehicles in traffic scenarios. Relying on the video information obtained from a stereo camera mounted on a moving vehicle, we first determin...
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Let $$G=(V, E)$$ be a graph. Denote $$d_G(u, v)$$ the distance between two vertices $$u$$ and $$v$$ in $$G$$ . An $$L(2, 1)$$ -labeling of $$G$$ is a function $$f: V \rightarrow \{0,1,\cdots \}$$ such that for any two...
Let $$G=(V, E)$$ be a graph. Denote $$d_G(u, v)$$ the distance between two vertices $$u$$ and $$v$$ in $$G$$ . An $$L(2, 1)$$ -labeling of $$G$$ is a function $$f: V \rightarrow \{0,1,\cdots \}$$ such that for any two vertices $$u$$ and $$v$$ , $$|f(u)-f(v)| \ge 2$$ if $$d_G(u, v) = 1$$ and $$|f(u)-f(v)| \ge 1$$ if $$d_G(u, v) = 2$$ . The span of $$f$$ is the difference between the largest and the smallest number in $$f(V)$$ . The $$\lambda $$ -number of $$G$$ , denoted $$\lambda (G)$$ , is the minimum span over all $$L(2,1 )$$ -labelings of $$G$$ . In this article, we confirm Conjecture 6.1 stated in X. Li et al. (J Comb Optim 25:716–736, 2013) in the case when (i) $$\ell $$ is even, or (ii) $$\ell \ge 5$$ is odd and $$0 \le r \le 8$$ .
As a key technology to implement Semantic Web, linked data have gradually been an academic and industrial concern. Linked data represents a practice of technologies on the web and linked structure data. The goal of li...
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As a key technology to implement Semantic Web, linked data have gradually been an academic and industrial concern. Linked data represents a practice of technologies on the web and linked structure data. The goal of linked data is to enable people to share structured data on the web as easily as they can share documents today. On the Web of data structured with linked data, users can jump from one dataset to another. Compared with the Web of document which enables one to jump from one document to another, data Web provides much more links and has semantics. Mapping relational databases to RDF is a fundamental problem for the development of linked data. This paper firstly makes an improvement with R2RML to open source software named D2R which can publish linked data, and then takes an example of the data concerning a college enrollment in Sichuan of China in 2011, demonstrating that we can publish the data in RDB into RDF as linked data through the new approach more efficient and make it browsable.
In this paper, we propose a robust visual tracking algorithm based on online learning of a joint sparse dictionary. The joint sparse dictionary consists of positive and negative sub-dictionaries, which model foregroun...
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The study provides a design scheme for the mountain landslide monitoring System based on wireless sensor networks. Different sensors are mainly used to collect data about the water depth in the soil and the sloping an...
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Segmentation becomes a difficult task if the objects are not homogeneous and have overlapping characteristics. The Graph Cuts methods combined with Gaussian Mixture Model (GMM) for initialization label has been adopte...
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Segmentation becomes a difficult task if the objects are not homogeneous and have overlapping characteristics. The Graph Cuts methods combined with Gaussian Mixture Model (GMM) for initialization label has been adopted to detect cattle object in an image with complex background. The RGB colors and Gray Level Co-occurrence Matrix (GLCM) textures are used as the features set. This method can robustly segment the cattle beef image from its background. This segmentation method produces the average of accuracy value up to 90%.
Asymmetric 3D-2D face recognition (FR) aims to recognize individuals from 2D face images using textured 3D face models in the gallery (or vice versa). This new FR scenario has the potential to be readily deployable in...
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