this paper aims to provide combination of multiple prediction models using different strategies including ensemble selection, voting, stacking and multi-schemes to design a model capable of predicting oil prices accur...
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ISBN:
(纸本)9781479959341
this paper aims to provide combination of multiple prediction models using different strategies including ensemble selection, voting, stacking and multi-schemes to design a model capable of predicting oil prices accurately. Daily data from 1999 to 2012 with 14 variables were used, which were further divided into 10 sub-datasets according to various attribute selection methods. Four groups of training and testing were examined. Experimental results conclude that performance of the combination model works better than author's previous work and ensemble selection outperforms other combination methods.
this paper presents an approach to distinguish a salient object from an image. In this paper, we have introduced a robust method to detect the salient object from an image. We have utilized local contrast and edge col...
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ISBN:
(纸本)9781728127910
this paper presents an approach to distinguish a salient object from an image. In this paper, we have introduced a robust method to detect the salient object from an image. We have utilized local contrast and edge color dissimilarity features to identify the salient regions. Firstly, Local contrast is used which is highly capable to extract the foreground salient object from background based on local contrast with its neighboring regions while foreground and background are more similar. Secondly, edge color dissimilarity measure helps to locate the salient region from other regions of an image having more cluttered background images. However, combination of local contrast and edge color dissimilarity features works better in salient region detection from an image. Experimental results demonstrate that proposed approach presents a good result which has been tested on two datasets ECSSD and SOD.
Deriving Branin's solution of uniform lossless transmission lines can be automated by using symbolic analysis and rewrite rules. this paper aims to show the derivation steps using SymPy, an application of this aut...
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the proceedings contain 94 papers. the special focus in this conference is on Analysis and Understanding. the topics include: On design and applications of cylindrical panoramas;finding the symmetry axis of a perspect...
ISBN:
(纸本)3540407308
the proceedings contain 94 papers. the special focus in this conference is on Analysis and Understanding. the topics include: On design and applications of cylindrical panoramas;finding the symmetry axis of a perspectively projected plane curve;representing orientation in n-dimensional spaces;docking of polygons using boundary descriptor;area and moment computation for objects with a closed spline boundary;construction of complete and independent systems of rotation moment invariants;a structural framework for assembly modeling and recognition;simple points in 2D and 3D binary images;planning optimal sequences of views for object recognition;epipolar plane images as a tool to seek correspondences in a dense sequence;computing neck-shaft angle of femur for X-ray fracture detection;rough surface correction and re-illumination using the modified beckmann model;towards a real time panoramic depth sensor;depth recovery from noisy gradient vector fields using regularization;bunch sampling for fast texture synthesis;automatic detection of specular reflectance in colour images using the MS diagram;skeletonization of character based on wavelet transform;a new sharpness measure based on gaussian lines and edges;object tracking and identification from motion;evaluation of an adaptive composite gaussian model in video surveillance;low complexity motion estimation based on spatio-temporal correlations and direction of motion vectors;stereo system for tracking moving object using log-polar transformation and zero disparity filtering and monte carlo visual tracking using color histograms and a spatially weighted oriented hausdorff measure.
A discussion on involvement of knowledge based methods in implementation of user friendly computer programs for disabled people is the goal of this paper. the paper presents a concept of a computer program that is aim...
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Dataflow computing is seen as an advantageous method for parallel processing and provides efficiency in CPU intensive applications. the Network-on-Chip (NoC) is an integrated communication framework that employs route...
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Detecting pattern in images plays a huge role in the field of computer vision. the article summarizes methods for detecting patterns by their properties, such as colours, shapes in images. And with video, the detectio...
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the paper presents preliminary results of data analysis and discusses the application of soft computing methods in the field of non-destructive tests. the main objective of developed diagnostic system are the automati...
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ISBN:
(纸本)9783642132315
the paper presents preliminary results of data analysis and discusses the application of soft computing methods in the field of non-destructive tests. the main objective of developed diagnostic system are the automatic detection and evaluation of damage. thus the system is composed of two signal processing techniques known as novelty detection and patternrecognition. For this purpose autoassociative as well as feed-forward neural networks are used. All the signals used for training the system are obtained from laboratory tests of strip specimens, where phenomenon of elastic wave propagation in solids was utilized. Computed parameters of time signals defines various types of input vectors used for training neural networks. the results finally obtained prove that the proposed diagnostic system made automation of structure testing possible and can be applied to Structural Health Monitoring.
Increasingly, distributed systems are being constructed by composing a number of discrete components. this practice, termed composition, is particularly prevalent within the Web service domain. Here, enterprise system...
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In this work, we study the problems of computing spatially continuous cuts, which has many important applications of image processing and computer vision. We focus on the convex relaxed formulations and investigate th...
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ISBN:
(纸本)9783319146126;9783319146119
In this work, we study the problems of computing spatially continuous cuts, which has many important applications of image processing and computer vision. We focus on the convex relaxed formulations and investigate the corresponding flow-maximization based dual formulations. We propose a series of novel continuous max-flow models based on evaluating different constraints of flow excess, where the classical pre-flow and pseudo-flow models over graphs are re-discovered in the continuous setting and re-interpreted in a new variational manner. We propose a new generalized proximal method, which is based on a specific entropic distance function, to compute the maximum flow. this leads to new algorithms exploring flow-maximization and message-passing simultaneously. We show the proposed algorithms are superior to state of art methods in terms of efficiency.
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