Relevant bibliographies by topics / Bayes fusion rule

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  3. Conference papers

Academic literature on the topic 'Bayes fusion rule'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Bayes fusion rule"

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Ibrahim, Ahmed Saleh, Ibrahim Alsaif Omar, and A. Yahya Maan. "Optimal distributed decision in wireless sensor network using gray wolf optimization." International Journal of Artificial Intelligence (IJ-AI) 9, no. 4 (2020): 646–54. https://doi.org/10.11591/ijai.v9.i4.pp646-654.

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The distributed object decision (DOD) was applied to choose a single solution for problem among many complexes solutions. Most of DOD systems depend on traditional technique like small form factor optical (SFFO) method and scalable and oriented fast-based local features (SOFF) method. These two methods were statistically complex and depended to an initial value. In this paper proposed new optimal technical called gray wolf optimization (GWO) which is used to determine threshold of sensor decision rules from fusion center. The new algorithm gave better performance for fusion rule than numerical
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Saleh, Ibrahim Ahmed, Omar Ibrahim Alsaif, and Maan A. Yahya. "Optimal distributed decision in wireless sensor network using gray wolf optimization." IAES International Journal of Artificial Intelligence (IJ-AI) 9, no. 4 (2020): 646. http://dx.doi.org/10.11591/ijai.v9.i4.pp646-654.

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<p class="Default">The distributed object decision (DOD) was applied to choose a single solution for problem among many complexes solutions. Most of DOD systems depend on traditional technique like small form factor optical (SFFO) method and scalable and oriented fast-based local features (SOFF) method. These two methods were statistically complex and depended to an initial value. In this paper proposed new optimal technical called gray wolf optimization (GWO) which is used to determine threshold of sensor decision rules from fusion center. The new algorithm gave better performance for f
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Dong, Xiangxiang, Luigi Chisci, and Yunze Cai. "An Adaptive Filter for Nonlinear Multi-Sensor Systems with Heavy-Tailed Noise." Sensors 20, no. 23 (2020): 6757. http://dx.doi.org/10.3390/s20236757.

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Aiming towards state estimation and information fusion for nonlinear systems with heavy-tailed measurement noise, a variational Bayesian Student’s t-based cubature information filter (VBST-CIF) is designed. Furthermore, a multi-sensor variational Bayesian Student’s t-based cubature information feedback fusion (VBST-CIFF) algorithm is also derived. In the proposed VBST-CIF, the spherical-radial cubature (SRC) rule is embedded into the variational Bayes (VB) method for a joint estimation of states and scale matrix, degree-of-freedom (DOF) parameter, as well as an auxiliary parameter in the nonli
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Hou, Yuan Bin, Mao Quan Zheng, Xin Zhao Wang, and Ya Li Xue. "The Belt Conveyor Control of Large Dip Angle by FMBTES." Advanced Materials Research 905 (April 2014): 452–58. http://dx.doi.org/10.4028/www.scientific.net/amr.905.452.

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Based on the analysis of dynamic characteristics of the belt conveyor with the long distance and the large dip angle in coal mine, a kind fusion method of Bayes theory and expert system (FMBTES) is proposed which is control method with the change regular of the start process. First, the structure and dynamics model are established for belt conveyor, the priori distributions of the system implementation state is supposed, the conditional probability of dynamics state is made using Bayes theory, next, the change regular of the start process pull force is found, and the change regular of the dyna
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Zhu, Wenjing, Shoufeng Shen, and Zhijun Zhang. "Improved Multiclassification of Schizophrenia Based on Xgboost and Information Fusion for Small Datasets." Computational and Mathematical Methods in Medicine 2022 (July 19, 2022): 1–11. http://dx.doi.org/10.1155/2022/1581958.

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To improve the performance in multiclass classification for small datasets, a new approach for schizophrenic classification is proposed in the present study. Firstly, the Xgboost classifier is introduced to discriminate the two subtypes of schizophrenia from health controls by analyzing the functional magnetic resonance imaging (fMRI) data, while the gray matter volume (GMV) and amplitude of low-frequency fluctuations (ALFF) are extracted as the features of classifiers. Then, the D-S combination rule of evidence is used to achieve fusion to determine the basic probability assignment based on t
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Mourad, Moussa. "An iterative algorithm for color space optimization on image segmentation." TELKOMNIKA Telecommunication, Computing, Electronics and Control 19, no. 1 (2021): pp. 199~205. https://doi.org/10.12928/TELKOMNIKA.v19i1.15122.

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This paper proposes, a novel hybrid color component (HCC) issued from amounts number of color space with iterative manner, in fact traditional images obtained by RGB sensor weren’t the effective way in image processing applications, for this purpose we have propose a supervised algorithm to substitute RGB level by hybrid and suitable color space at the aim to make well representation of the handled amounts of data, this step is extremely important because the obtained results it will be injected in many future studies like tracking, classification, steganography and cryptography. The sec
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Mostafiz, Rafid, Mohammad Rahman, A. Islam, and Saeid Belkasim. "Focal Liver Lesion Detection in Ultrasound Image Using Deep Feature Fusions and Super Resolution." Machine Learning and Knowledge Extraction 2, no. 3 (2020): 172–91. http://dx.doi.org/10.3390/make2030010.

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This research presents a machine vision approach to detect lesions in liver ultrasound as well as resolving some issues in ultrasound such as artifacts, speckle noise, and blurring effect. The anisotropic diffusion is modified using the edge preservation conditions which found better than traditional ones in quantitative evolution. To dig for more potential information, a learnable super-resolution (SR) is embedded into the deep CNN. The feature is fused using Gabor Wavelet Transform (GWT) and Local Binary Pattern (LBP) with a pre-trained deep CNN model. Moreover, we propose a Bayes rule-based
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Lian, Feng, Liming Hou, Jing Liu та Chongzhao Han. "Constrained Multi-Sensor Control Using a Multi-Target MSE Bound and a δ-GLMB Filter". Sensors 18, № 7 (2018): 2308. http://dx.doi.org/10.3390/s18072308.

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The existing multi-sensor control algorithms for multi-target tracking (MTT) within the random finite set (RFS) framework are all based on the distributed processing architecture, so the rule of generalized covariance intersection (GCI) has to be used to obtain the multi-sensor posterior density. However, there has still been no reliable basis for setting the normalized fusion weight of each sensor in GCI until now. Therefore, to avoid the GCI rule, the paper proposes a new constrained multi-sensor control algorithm based on the centralized processing architecture. A multi-target mean-square e
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Schmidt-Richberg, A., J. Fiehler, T. Illies, et al. "Fuzzy-based Vascular Structure Enhancement in Time-of-Flight MRA Images for Improved Segmentation." Methods of Information in Medicine 50, no. 01 (2011): 74–83. http://dx.doi.org/10.3414/me10-02-0003.

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Summary Objectives: Cerebral vascular malformations might lead to strokes due to occurrence of ruptures. The rupture risk is highly related to the individual vascular anatomy. The 3D Time-of-Flight (TOF) MRA technique is a commonly used non-invasive imaging technique for exploration of the vascular anatomy. Several clinical applications require exact cerebrovascular segmentations from this image sequence. For this purpose, intensity-based segmentation approaches are widely used. Since small low-contrast vessels are often not detected, vesselness filter-based segmentation schemes have been prop
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Hu, Xue Hai, Hou Jun Wang, Dai Rong Ren, and Cheng Gong. "Optimization of Distributed Systems' Fusion Based on Climb-Ant Algorithm." Applied Mechanics and Materials 483 (December 2013): 524–28. http://dx.doi.org/10.4028/www.scientific.net/amm.483.524.

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This paper proposes an optimization algorithm which combines climb algorithm and ant algorithm and use it to solve optimization problems of fusion rules in distributed detection systems .Firstly, algorithm takes Bayes risk as the cost function, uses Climb-ant algorithm to optimize the sensors' decision threshold and Bayes criteria to solve the fusion rules of fusion center. Ultimately, we get the system's optimal (or suboptimal) fusion rules and realize the optimization of fusion rules in distributed detection system. Theoretical analysis and experimental results show that the new method has h
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Book chapters on the topic "Bayes fusion rule"

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Palmieri Francesco and Ciuonzo Domenico. "Data Fusion with Entropic Priors." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2011. https://doi.org/10.3233/978-1-60750-692-8-107.

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In classification problems, lack of knowledge of the prior distribution may make the application of Bayes' rule inadequate. Uniform or arbitrary priors may often provide classification answers that, even in simple examples, may end up contradicting our common sense about the problem. Entropic priors, determined via the application of the maximum entropy principle, seem to provide a much better answer and can be easily derived and applied to classification tasks when no more than the likelihood functions are available. In this paper we present an example in which the use of the entropic priors
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Conference papers on the topic "Bayes fusion rule"

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El-Fallah, A., A. Zatezalo, R. Mahler, and R. K. Mehra. "Unified robust-Bayes multisource ambiguous data rule fusion." In Defense and Security, edited by Ivan Kadar. SPIE, 2005. http://dx.doi.org/10.1117/12.605466.

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Wu, Yunfeng, and S. C. Ng. "Combining Neural Learners with the Naive Bayes Fusion Rule for Breast Tissue Classification." In 2007 2nd IEEE Conference on Industrial Electronics and Applications. IEEE, 2007. http://dx.doi.org/10.1109/iciea.2007.4318498.

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Tallman, Aaron E., Joel D. Blumer, Yan Wang, and David L. McDowell. "Multiscale Model Validation Based on Generalized Interval Bayes’ Rule and its Application in Molecular Dynamics Simulation." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-35126.

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Reliable simulation protocols supporting integrated computational materials engineering requires uncertainty to be quantified. In general, two types of uncertainties are recognized. Aleatory uncertainty is inherent randomness, whereas epistemic uncertainty is due to lack of knowledge. Aleatory and epistemic uncertainties need to be differentiated in validating multiscale models, where measurement data for unconventionally very small or large systems are scarce, or vary greatly in forms and quality (i.e. sources of epistemic uncertainty). In this paper, a recently proposed generalized hidden Ma
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Wang, Meng, and Jian Yang. "Multi-sensor image fusion with ICA bases and region rule." In 2008 10th International Conference on Control, Automation, Robotics and Vision (ICARCV 2008). IEEE, 2008. http://dx.doi.org/10.1109/icarcv.2008.4795865.

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Andov, Stojan, Violeta Cvetkoska, and Tea Mijac. "Unveiling Global Road Accident Patterns - Insights, Analytics, and Implications for Safer Driving Practices." In Economic and Business Trends Shaping the Future. Ss Cyril and Methodius University, Faculty of Economics-Skopje, 2023. http://dx.doi.org/10.47063/ebtsf.2023.0031.

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Every day, we are confronted with alarming news of serious injuries and fatalities resulting from car accidents. In the past decade, these incidents have been on the rise, posing a significant concern for individuals and societies worldwide. The impact of these accidents is particularly devastating when innocent lives, including children, are affected by the long-lasting consequences. While driver behavior remains a major contributing factor to road accidents, there are also other indirect reasons such as infrastructure issues and weather conditions. Addressing this global problem is of utmost
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Journal articles
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