Relevant bibliographies by topics / EDGE BASED WEIGHTING

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  1. Journal articles
  2. Dissertations / Theses
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  4. Conference papers
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Academic literature on the topic 'EDGE BASED WEIGHTING'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "EDGE BASED WEIGHTING"

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Li, Xian Mao, Gao Ming Huang, and Dong Xia. "Spacial Filter of Weighting Method Based on Spectrum Analyse." Advanced Materials Research 605-607 (December 2012): 1890–96. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.1890.

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The selection of a certain scope angle signal in the traditional method is to switch the hard switches in antennas, this paper proposes a method, which based on a weighting method to filter the signal in certain directions, namely spacial filter. With array antennas，the compositive signal can be acquired, by which the phrase and plus (weighting) of each unit antenna’s signal be adjusted and then the signals be added. In different time, signals can be selected in any scope of directions through adjusting each channels by different weighting. The weighting parameters can be obtained through the analysis of spacial signal and spacial spectrum, and then obtains an appropriate weighting window function. Simulation shows that Hamming window’s weighting is the best among the three representative windows functions. It can obtain a low sidelobe (-44dB) and less rising edge and declining edges. And the paper also give a hardware structure.
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Karasuyama, Masayuki, and Hiroshi Mamitsuka. "Adaptive edge weighting for graph-based learning algorithms." Machine Learning 106, no. 2 (November 18, 2016): 307–35. http://dx.doi.org/10.1007/s10994-016-5607-3.

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KERR, GRAINNE, DIMITRI PERRIN, HEATHER J. RUSKIN, and MARTIN CRANE. "EDGE-WEIGHTING OF GENE EXPRESSION GRAPHS." Advances in Complex Systems 13, no. 02 (April 2010): 217–38. http://dx.doi.org/10.1142/s0219525910002505.

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In recent years, considerable research efforts have been directed to micro-array technologies and their role in providing simultaneous information on expression profiles for thousands of genes. These data, when subjected to clustering and classification procedures, can assist in identifying patterns and providing insight on biological processes. To understand the properties of complex gene expression datasets, graphical representations can be used. Intuitively, the data can be represented in terms of a bipartite graph, with weighted edges corresponding to gene-sample node couples in the dataset. Biologically meaningful subgraphs can be sought, but performance can be influenced both by the search algorithm, and, by the graph-weighting scheme and both merit rigorous investigation. In this paper, we focus on edge-weighting schemes for bipartite graphical representation of gene expression. Two novel methods are presented: the first is based on empirical evidence; the second on a geometric distribution. The schemes are compared for several real datasets, assessing efficiency of performance based on four essential properties: robustness to noise and missing values, discrimination, parameter influence on scheme efficiency and reusability. Recommendations and limitations are briefly discussed.
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Seo, Suyoung. "Subpixel Edge Localization Based on Adaptive Weighting of Gradients." IEEE Transactions on Image Processing 27, no. 11 (November 2018): 5501–13. http://dx.doi.org/10.1109/tip.2018.2860241.

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Cheng Deqiang, 程德强, 庄焕东 Zhuang Huandong, 于文洁 Yu Wenjie, 白春梦 Bai Chunmeng, and 文小顺 Wen Xiaoshun. "Cross-Scale Local Stereo Matching Based on Edge Weighting." Laser & Optoelectronics Progress 56, no. 21 (2019): 211504. http://dx.doi.org/10.3788/lop56.211504.

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Sun, Peng Gang. "Weighting links based on edge centrality for community detection." Physica A: Statistical Mechanics and its Applications 394 (January 2014): 346–57. http://dx.doi.org/10.1016/j.physa.2013.08.048.

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Kovács, László, Anita Agárdi, and Tamás Bányai. "Fitness Landscape Analysis and Edge Weighting-Based Optimization of Vehicle Routing Problems." Processes 8, no. 11 (October 28, 2020): 1363. http://dx.doi.org/10.3390/pr8111363.

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Vehicle routing problem (VRP) is a highly investigated discrete optimization problem. The first paper was published in 1959, and later, many vehicle routing problem variants appeared to simulate real logistical systems. Since vehicle routing problem is an NP-difficult task, the problem can be solved by approximation algorithms. Metaheuristics give a “good” result within an “acceptable” time. When developing a new metaheuristic algorithm, researchers usually use only their intuition and test results to verify the efficiency of the algorithm, comparing it to the efficiency of other algorithms. However, it may also be necessary to analyze the search operators of the algorithms for deeper investigation. The fitness landscape is a tool for that purpose, describing the possible states of the search space, the neighborhood operator, and the fitness function. The goal of fitness landscape analysis is to measure the complexity and efficiency of the applicable operators. The paper aims to investigate the fitness landscape of a complex vehicle routing problem. The efficiency of the following operators is investigated: 2-opt, order crossover, partially matched crossover, cycle crossover. The results show that the most efficient one is the 2-opt operator. Based on the results of fitness landscape analysis, we propose a novel traveling salesman problem genetic algorithm optimization variant where the edges are the elementary units having a fitness value. The optimal route is constructed from the edges having good fitness value. The fitness value of an edge depends on the quality of the container routes. Based on the performed comparison tests, the proposed method significantly dominates many other optimization approaches.
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Mahajan, Shveta, Anu Rani, Mamta Sharma, Sudesh Kumar Mittal, and Amitava Das. "A pre-processing based optimized edge weighting method for colour constancy." Imaging Science Journal 66, no. 4 (December 15, 2017): 231–38. http://dx.doi.org/10.1080/13682199.2017.1412889.

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Tan, Xiao, Changming Sun, and Tuan D. Pham. "Edge-Aware Filtering with Local Polynomial Approximation and Rectangle-Based Weighting." IEEE Transactions on Cybernetics 46, no. 12 (December 2016): 2693–705. http://dx.doi.org/10.1109/tcyb.2015.2485203.

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Zheng, Yi, Fang Liu, and Yong-Wang Gong. "Robustness in Weighted Networks with Cluster Structure." Mathematical Problems in Engineering 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/292465.

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The vulnerability of complex systems induced by cascade failures revealed the comprehensive interaction of dynamics with network structure. The effect on cascade failures induced by cluster structure was investigated on three networks, small-world, scale-free, and module networks, of which the clustering coefficient is controllable by the random walk method. After analyzing the shifting process of load, we found that the betweenness centrality and the cluster structure play an important role in cascading model. Focusing on this point, properties of cascading failures were studied on model networks with adjustable clustering coefficient and fixed degree distribution. In the proposed weighting strategy, the path length of an edge is designed as the product of the clustering coefficient of its end nodes, and then the modified betweenness centrality of the edge is calculated and applied in cascade model as its weights. The optimal region of the weighting scheme and the size of the survival components were investigated by simulating the edge removing attack, under the rule of local redistribution based on edge weights. We found that the weighting scheme based on the modified betweenness centrality makes all three networks have better robustness against edge attack than the one based on the original betweenness centrality.
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Dissertations / Theses on the topic "EDGE BASED WEIGHTING"

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BHAGYANIDHI. "HAZE REMOVAL AND DETAIL ENHANCEMNT ALGORITHM USING GLOBALLY GUIDED FILTERING." Thesis, 2018. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16406.

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Nowadays, the utilization and demand of image filters is very high in various applications of the areas of computer vision and image processing. Many local edge preserving smoothing strategies including Guided Filter [2] and Weighted Guided Filter [3] have been proposed in the literature earlier. These have been applied for studying different applications such as detail enhancement, de-hazing, feathering and many more. But these techniques may fail to preserve fine structured regions. A new technique, i.e. globally guided filtering has been introduced for solving this issue. In this study, I utilized the functionality of globally guided filter [1] in the de-hazing application as well as for the detail enhancement of the images. We have proposed a model for detail enhancement using globally guided filtering by incorporating edge-based weighting in it. Initially, a model was designed which was based on decomposition algorithm for detail enhancement. Then, the results are obtained for both of the algorithm models and compared. Whereas this model is having some limitation including noise amplification in flat patch areas and halo artifacts on edges. Therefore, edge-based weighting is incorporated to resolve this issue.
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Book chapters on the topic "EDGE BASED WEIGHTING"

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Kwon, JuHum, Chang-Joo Moon, Soo-Hyun Park, and Doo-Kwon Baik. "Measuring Semantic Similarity Based on Weighting Attributes of Edge Counting." In Lecture Notes in Computer Science, 470–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-30583-5_50.

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Conference papers on the topic "EDGE BASED WEIGHTING"

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Park, Sang-Jun, Changki Min, Jechang Jeong, and Gwanggil Jeon. "Adaptive Weighting Scheme for Edge-based Line Interpolation." In 2010 Fourth Pacific-Rim Symposium on Image and Video Technology (PSIVT). IEEE, 2010. http://dx.doi.org/10.1109/psivt.2010.60.

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Canh, Thuong Nguyen, Khanh Quoc Dinh, and Byeungwoo Jeon. "Edge-preserving nonlocal weighting scheme for total variation based compressive sensing recovery." In 2014 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2014. http://dx.doi.org/10.1109/icme.2014.6890251.

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Albano, James A., Amanda K. Ziemann, and David W. Messinger. "Assessing the impact of the edge-weighting function in a graph-based approach to anomaly detection." In 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2013. http://dx.doi.org/10.1109/whispers.2013.8080603.

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Chen, Yue, Debargha Mukherjee, Jingning Ean, and Kenneth Rose. "Joint inter-intra prediction based on mode-variant and edge-directed weighting approaches in video coding." In ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2014. http://dx.doi.org/10.1109/icassp.2014.6855032.

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Sun, Haobo, Yu Zhu, Kaiming Yang, and Sen Lu. "Edge Coil Force Fitting and Current Optimal Commutation Algorithm for Magnetic Levitation Planar Motor With Moving Magnet." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23534.

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Abstract In this paper, edge coils are added to the commutation algorithm of the coil array. In order to reduce the theoretical modeling error of the edge coil force, a method of edge coil force fitting based on radial basis function (RBF) network is proposed. The obtained attenuation function of edge force can replace the weighting function in the switching algorithm, so it can effectively reduce the current density of the central coils and the heat loss power of the coil array. On this basis, a non-iterative current optimal commutation algorithm is proposed. The algorithm takes the weighted sum of the 2-norm of the coil current and the 2-norm of the difference between the coil current and the saturation current as the optimization objective, and obtains the analytical expression of the instantaneous current by solving the Karush Kuhn Tucker (KKT) equation. The results of simulation show that, compared with the direct decoupling algorithm with weighting function, the proposed commutation algorithm can reduce the heat loss power of the coil array and allow the translator to provide greater acceleration under the same maximum current limitation.
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Kugaevskikh, A. V., and A. D. Mangarakov. "Bio-inspired Neuron Model for Motion Detection on Base Signal Accumulation." In 32nd International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2022. http://dx.doi.org/10.20948/graphicon-2022-568-576.

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The article presents a new model of the MT neuron (neuron of the middle temporal region), which allows motion detecting and determining its direction and speed without the use of recurrent communication. The model is based on signal accumulation and is organized using a space-time vector that sets the weighting coefficients. The space-time vector is formed using the product of the Gaussian, which defines the spatial component, and the "Mexican hat" wavelet, which sets the time vector of the change in the receptive field. This configuration allows not only to motion detect, but also to make the model not sensitive to uniform or textural fill. The model is presented in variants for determining linear and rotational motion. Motion, in this case, is the sequential activation of several edge selection neurons located in the same direction in a certain neighborhood over time i.e. with a change of frame. To assess the motion, the models were tested on the MPI Sintel dataset. The model developed by us shows results better than Spatio-Temporal Gabor. The best accuracy of determining the direction of movement can be obtained with the size of the space-time vector (7*7, 7).
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Tınaztepe, H. Tug˘rul, Ahmet S¸ U¨c¸er, and I˙ Sinan Akamandor. "Performance Evaluation of an Internal Flow Navier-Stokes Solver for Compressible Viscous Flow Simulations." In ASME Turbo Expo 2002: Power for Land, Sea, and Air. ASMEDC, 2002. http://dx.doi.org/10.1115/gt2002-30681.

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A three-dimensional compressible full Navier-Stokes solver is developed for the analysis of the flow field inside turbomachinary cascades. The solver uses an explicit second order accurate (cell-vertex) finite volume Lax-Wendroff scheme over hexahedral cells. The viscous and heat conduction terms are discretized in conservative form at the cell center. Second and fourth order numerical smoothing terms are added with local scaling factors. Eddy viscosity is calculated by the Baldwin-Lomax model and is adapted to the pointered cell based algorithm. Turbulent viscosity is blended by inverse distance square weighting functions near corners. Characteristic boundary conditions are used. A computational analysis has been carried out to present the capability of the solver in capturing secondary velocity patterns, flow angles and total pressure loss distributions inside a linear high turning turbine cascade. A controlled diffusion compressor cascade at high incidence has been analyzed. Main features of the flow field in this compressor cascade were resolved (secondary and end wall flows and leading edge laminar separation bubble) as in the experimental data. The main aim of the work is to demonstrate the performance of the code in capturing the details of the complicated flow fields using grids that can be regarded as coarse.
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Reports on the topic "EDGE BASED WEIGHTING"

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Yoo, Andy, Geoffrey Sanders, Van Henson, and Panayot Vassilevski. Enhancing Community Detection By Affinity-based Edge Weighting Scheme. Office of Scientific and Technical Information (OSTI), October 2015. http://dx.doi.org/10.2172/1226950.

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Journal articles
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