We present a novel method for correcting the significance level of hypothesis testing that requires multiple comparisons. It is based on the spectral graph theory, in which the variables are seen as the vertices of a ...
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We present a novel method for correcting the significance level of hypothesis testing that requires multiple comparisons. It is based on the spectral graph theory, in which the variables are seen as the vertices of a complete undirected graph and the correlation matrix as the adjacency matrix that weights its edges. the method increases the statistical power of the analysis by refuting the assumption of independence among variables, while keeping the probability of false positives low. By computing the eigenvalues of the correlation matrix, it is possible to obtain valuable information about the dependence levels among the variables of the problem, so that the effective number of independent variables can be estimated. the method is compared to other available models and its effectiveness illustrated in case studies involving high-dimensional sets of variables.
image segmentation using tree pruning (TP) and watershed (WS) has been presented in the framework of the image forest transform (IFT)- a method to reduce imageprocessing problems related to connectivity into an optim...
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Surface representation and processing is one of the key topics in computergraphics and geometric modeling, since it greatly affects the range of possible applications. In this paper we will present recent advances in...
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Surface representation and processing is one of the key topics in computergraphics and geometric modeling, since it greatly affects the range of possible applications. In this paper we will present recent advances in geometry processingthat are related to the Laplacian processing framework and differential representations. this framework is based on linear operators defined oil polygonal meshes, and furnishes a variety of processing applications, such as shape approximation and compact representation, mesh editing, watermarking and morphing. the core of the framework is the definition of differential coordinates and new bases for efficient mesh geometry representation, based on the mesh Laplacian operator.
Traditional mesh segmentation methods normally operate on geometrical models with no image information. On the other hand, 2D image-based mesh generation and segmentation counterparts, such as Imesh [6] perform the ta...
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In this paper, we propose different criteria for detecting unusual motion in surveillance cameras. Initially, a certain environment is observed within a time interval, and captured trajectories are used as examples of...
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the article provides information on the Afrigraph organization in Africa. the purpose of Afrigraph is to help consolidate and promote the practice of relevant computergraphics in academia, arts and industry in Africa...
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the article provides information on the Afrigraph organization in Africa. the purpose of Afrigraph is to help consolidate and promote the practice of relevant computergraphics in academia, arts and industry in Africa. Afrigraph has run a series of four international conferences in order to foster the computergraphics community in Africa and international cooperation. the organization held a graphics programming contst open to school pupils in Southern Africa as a new venture in 2006.
the map-seeking circuit (MSC) is an explicit biologically-motivated computational mechanism which provides practical solution of problems in object recognition, image registration and stabilization, limb inverse-kinem...
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the map-seeking circuit (MSC) is an explicit biologically-motivated computational mechanism which provides practical solution of problems in object recognition, image registration and stabilization, limb inverse-kinematics and other inverse problems which involve transformation discovery. We formulate this algorithm as discrete dynamical system on a set Delta = Pi(L)(l=1)Delta((l)), where each Delta((l)) is a compact subset of a nonnegative orthant of R-n, and show that for an open and dense set of initial conditions in Delta the corresponding solutions converge to either a vector with unique nonzero element in each Delta((l)) or to a zero vector. the first result implies that the circuit finds a unique best mapping which relates reference pattern to a target pattern;the second result is interpreted as "no match found". these results verify numerically observed behavior in numerous practical applications.
We present a method for evaluating COVID-19 contamination risk based on social distancing between individuals and face mask usage. Our method employs images captured by surveillance cameras as input to a system that c...
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ISBN:
(数字)9781665453851
ISBN:
(纸本)9781665453851
We present a method for evaluating COVID-19 contamination risk based on social distancing between individuals and face mask usage. Our method employs images captured by surveillance cameras as input to a system that computes a health risk indicator in real time. this system can handle real-world situations, performing detections in large public spaces, such as squares and streets, as well as other potentially crowded areas like restaurants and shopping centers. Our system uses the number of people with and without masks and their proximity to evaluate the risk of COVID-19 contamination. We employed deep neural networks to detect people with and without masks, and we used computer vision to measure the distance between them. Both cases presented challenges, including distinguishing face masks at wildly different distances and positions concerning the camera, occlusions, shape variance, etc. We have built and made public a face mask detection dataset (44,402 faces) withimages that include these challenging scenarios and used them to train our deep neural networks. Our best deep neural network architecture achieved 91.41% precision, 82.88% accuracy, and 89.88% recall on face mask detection.
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