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The strategies for the preservation of historical documents can include their digitization, which is an effective way to make them publicly available while preventing degradation of the original sources. The Arquivo Publico Mineiro (APM), the Archives of the State of Minas Gerais, has a collection of historical photographs from Brazil, and some of them have been digitized. The availability of digital...
Sampled vector fields generally appear as measurements of real phenomena. They can be obtained by the use of a particle image velocimetry acquisition device, or as the result of a physical simulation, such as a fluid flow simulation, among many examples. This paper proposes to formulate the unstructured vector field reconstruction and approximation through Machine-Learning. The machine learns from...
In this paper, we present a current mode CMOS image sensor with programmable convolution kernels consuming 35 mW of power and operating at 30 frames per second. The image sensor is composed of a 128 by 109 pixel array, digital scanning registers, and a programmable analog processing unit. Convolution of the image is performed on the read-out in the periphery of the image array using digitally programmable...
Multiscale approaches have been largely considered in several signal processing applications. They play an important role when designing automatic methods to cope with real world measurements where, in most of the cases, there is no prior information about which would be the appropriate scale. The basic idea behind a multiscale analysis is to embed the original signal into a family of derived signals,...
A class of large-scale stochastic discrete-time continuous-opinion dynamical systems is analyzed. Agents have pairwise random interactions in which their vector-valued opinions are updated to a weighted average of their current values. The intensity of the interactions is allowed to depend on the agents' opinions themselves through an interaction kernel. This class of models includes as a special...
In this paper, we present a novel context modeling (CM) architecture used in JPEG2000 encoder targeting next generation of cameras. The implementation is based on a newly emerging coarse-grained dynamically reconfigurable (DR) processor. A novel partial parallel architecture for the CM is introduced which can be easily tailored for the target DR processor in order to achieve higher performance results...
This paper presents a video shot boundary detection system based on support vector machine (SVM) classification method. A hardware fully-parallel digital support vector machine (SVM) classifier is used to detect the shot boundary in a continuous video stream. The throughput is increased by employing a pipelined architecture in the feature extraction stage. Hardware SVM can detect both cut and gradual...
The posterior matching scheme is known to achieve capacity for a large class of memoryless channels with noiseless feedback. In this contribution, it is shown that whenever the posterior matching kernel admits a fixed point, the corresponding scheme is not ergodic and cannot achieve any positive rate. The source of the problem is traced back to the input ordering implicit in the definition of the...
Recently ensemble classification has attracted serious attention of machine learning community as a solution for improving classification accuracy. The effect of the strategies for generating the members, combining the predictions and the size of the ensemble on the accuracy of the ensemble are of utmost interest to the researchers. In this paper, we propose and empirically evaluate a novel method...
Notwithstanding the extensive research effort has gone into understanding face perception by human brain. The concept of face recognition is established yet is selectively impaired relative to recognition of faces of equivalent difficulty. The objective of present study is to develop a theoretical model and a set of stipulations for understanding and discussing how we distinguish familiar faces, and...
Locating and identifying complex objects in a visual scene is a typical problem within the areas of computer vision and image analysis. One technique to minimise the size of image to be identified is to base the classification on smaller features of the image, which are combined into a more complex structure to identify the complete object. For example, locating two eyes, a nose and a mouth can enable...
Dynamic model error and observation model error was the main factor to badly pollute the precision of orbit determination, especially in space based observation. Model error compensation technology was researched by designing semi-parametric orbit determination regression model. Stahel-Donoho Kernel estimator was applied to solve the semi-parametric model, which can effectively estimate the model...
In this paper, we propose an efficient method to compute the optimal discriminant vectors of Generalized Discriminant Analysis (GDA) for face recognition tasks. The optimal discriminative features of face images are obtained by directly performing the kernel Gram-Schmidt orthogonalization procedure on the difference vectors only once. The theoretical justification is presented. The nonlinear difference...
Because logistics system was an uncertain, nonlinear, dynamic and complicated system, it was difficult to describe it by traditional methods. The support vector machine (SVM) has the ability of strong nonlinear function approach, it has the ability of strong generalization and it also has the feature of global optimization. In this paper, a modeling and forecasting method of urban logistics demand...
Enterprise performance evaluation is an important means of enterprise management, which can diagnose the whole development status of enterprise. Data envelopment analysis (DEA) is one of the most frequently used evaluation methods and support vector machine (SVM) is a novel method of data mining, which can be used for prediction and regression. Based on DEA and SVM, the paper proposes a method for...
A new method based on kernel which can measure class separability in feature space is proposed in this paper for existing error accumulation when the hierarchical SVMs is used to diagnose multiclass network fault. This method has defined metrics of sample distribution in feature space, which are used as the rule of constructing hierarchical SVMs. Experiment results show that this method can restrain...
Support vector machine is a new machine learning technique developed on the basis of statistical learning theory, which has become the hotspot of machine learning because of its excellent learning performance. Based on analyzing the theory of support vector machine for regression (SVR), a SVR model is established for predicting the output in fully mechanized mining face, and then realizes the model...
In this paper, we propose an efficient method for resolving the optimal discriminant vectors of generalized discriminant analysis (GDA) and point out the drawback of high computational complexity in the traditional class-incremental GDA [W. Zheng, "Class-Incremental Generalized Discriminant Analysis", Neural Computation 18, 979-1006 (2006)]. Because there is no need to compute the mean of...
To arrive at the goal of intensifying the trustworthiness and controllability of distributed systems, the core function of secure algorithms and chips should be fully exerted. Through building the trustworthy model between distributed system and user behaviors, constructing the architecture of trustworthiness distributed systems, intensifying the survivability of services, and strengthening the manageability...
Non-dedicated computer clusters promise more efficient resource utilization than conventional dedicated clusters. Existing non-dedicated clustering solutions either expect trust among participating users, or they do not take into account a possibility of running multiple independent clusters on a same set of computers.In this paper, we argue how an ability to run multiple independent clusters without...
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