Population-based search algorithms, such as the Differential Evolution approach, evolve a pool of candidate solutions during the optimization process and are suitable for massively parallel architectures promoted by t...
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作者：
De Almeida, FátimaCosta e Silva, ElianaCorreia, AldinaCIICESI
ESTG / P.PORTO - Center for Research and Innovation in Business Sciences and Information Systems School of Management and Technology/Polytechnic of Porto Margaride Felgueiras4610-156 Portugal
For assessing the structural features of organoclay C15A dispersions in PP/PP-g-MA melts under different processing conditions along the screws of Twin Screw Extruder, in this work four different clustering algorithms...
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the convergence of distributed parameter estimation algorithms is analyzed for a network of multiple nodes via information exchange with random observation matrices and communication graphs. Each node runs an online e...
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ISBN:
(纸本)9783907144022
the convergence of distributed parameter estimation algorithms is analyzed for a network of multiple nodes via information exchange with random observation matrices and communication graphs. Each node runs an online estimation algorithm consisting of a consensus term taking a weighted sum of its own estimate and the estimates of its neighbors, and an innovation term processing its own new measurement at each time step. By stochastic time-varying system, martingale convergence theories and the binomial expansion of random matrix products, the stochastic spatial-temporal persistence of excitation condition is established for mean square and almost sure convergence. Especially, it is shown that this condition holds for Markovian switching communication graphs and observation matrices, if the stationary graph is balanced with a spanning tree and the measurement model is spatially-temporally jointly observable. Furthermore, the quantitative bounds of mean square and almost sure convergence rates are both provided.
A new synthetic aperture radar (SAR) image denoising method based on fast weighted nuclear norm minimization (FWNNM) is proposed. SAR image is firstly modelled by a logarithmic additive model for modelling of the spec...
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ISBN:
(纸本)9789811365041;9789811365034
A new synthetic aperture radar (SAR) image denoising method based on fast weighted nuclear norm minimization (FWNNM) is proposed. SAR image is firstly modelled by a logarithmic additive model for modelling of the speckle. then, the non-local similarity is used for image block matching. Next, according to the framework of the low-rank model, randomized singular value decomposition (RSVD) is introduced to replace the singular value decomposition (SVD) in weighted nuclear norm minimization (WNNM) for approximating the low-rank matrix. Finally, the gradient histogram preservation (GHP) method is employed to enhance the texture of the image. Experiments on MSTAR database show that the proposed approach is effective in SAR image denoising and the edge preserving in comparison with some traditional algorithms. Moreover, it is three times faster than WNNM method.
the proceedings contain 214 papers. the special focus in this conference is on Intelligent systems Design and Applications. the topics include: Quantum Inspired High Dimensional Conceptual Space as KID Model for Elder...
ISBN:
(纸本)9783030166595
the proceedings contain 214 papers. the special focus in this conference is on Intelligent systems Design and Applications. the topics include: Quantum Inspired High Dimensional Conceptual Space as KID Model for Elderly Assistance;artificial Neural Networks: the Missing Link Between Curiosity and Accuracy;Metaheuristic for Optimize the India Speed Post Facility Layout Design and Operational Performance Based Sorting Layout Selection Using DEA Method;a Hybrid Evolutionary Algorithm for Evolving a Conscious Machine;a Cost Optimal Information Dispersal Framework for Cloud Storage System;multiple Sequence Alignment Using Chemical Reaction Optimization Algorithm;forensic Approach of Human Identification Using Dual Cross Pattern of Hand Radiographs;mixed Reality in Action - Exploring Applications for Professional Practice;AMGA: An Adaptive and Modular Genetic Algorithm for the Traveling Salesman Problem;hybrid Evolutionary Algorithm for Optimizing Reliability of Complex systems;Identification of Phishing Attack in Websites Using Random Forest-SVM Hybrid Model;Conflict Detection and Resolution with Local Search algorithms for 4D-Navigation in ATM;using Severe Convective Weather Information for Flight Planning;fault Tolerant Control Using Interval Type-2 Takagi-Sugeno Fuzzy Controller for Nonlinear System;a Semi-local Method for image Retrieval;physical Modeling of the Tread Robot and Simulated on Even and Uneven Surface;ipBF: A Fast and Accurate IP Address Lookup Using 3D Bloom Filter;From Dynamic UML/MARTE Models to Early Schedulability Analysis of RTES with Dependent Tasks;novel Authentication System for Personal and Domestic Network systems Using image Feature Comparison and Digital Signatures;improving Native Language Identification Model with Syntactic Features: Case of Arabic.
the space-Terrestrial information network integrates the characteristics of satellite networks and terrestrial networks and can support diversified space network requirements, which has also become a new trend in futu...
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We propose the original automated information technology for transformation of paper archives of drawing and design documentation into electronic 3D model of an object for CALS and BIM ideologies of designing and manu...
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ISBN:
(纸本)9781728170411
We propose the original automated information technology for transformation of paper archives of drawing and design documentation into electronic 3D model of an object for CALS and BIM ideologies of designing and manufacturing of an object. the technology assumes the full automated cycle of processing of projective kinds from initial paper drawings to electronic frame 3D model of an object. Original models of representation and algorithms of solving the given problem are proposed.
Handwritten recognition has received considerable attention in the domain of pattern recognition, imageprocessing, over the last few decades. As a consequence of this research effort, several algorithms were develope...
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ISBN:
(数字)9781728175744
ISBN:
(纸本)9781728175751
Handwritten recognition has received considerable attention in the domain of pattern recognition, imageprocessing, over the last few decades. As a consequence of this research effort, several algorithms were developed using different techniques. Particularly, Deep Learning has shown a remarkable capability to handle handwritten recognition in very recent years. the well-known Deep learning techniques are the Convolutional Neuronal Networks (CNNs) and Recurrent Neuronal Networks (RNNs). this paper provides a survey of the most recent handwritten recognition systems. thus, we present the most significant algorithms for handwritten character/word/text recognition by explaining the different approaches used in the recognition process and we compare them in terms of accuracy.
this paper offers a new feature-oriented compression algorithm for flexible reduction of data redundancy commonly found in images and videos streams. Using a combination of image segmentation and face detection techni...
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ISBN:
(数字)9781728175744
ISBN:
(纸本)9781728175751
this paper offers a new feature-oriented compression algorithm for flexible reduction of data redundancy commonly found in images and videos streams. Using a combination of image segmentation and face detection techniques as a preprocessing step, we derive a compression framework to adaptively treat `feature' and `ground' while balancing the total compression and quality of `feature' regions. We demonstrate the utility of a feature compliant compression algorithm (FC-SVD), a revised peak signal-to-noise ratio PSNR assessment, and a relative quality ratio to control artificial distortion. the goal of this investigation is to provide new contributions to image and video processing research via multi-scale resolution and the block-based adaptive singular value decomposition.
the infinite variety of image subjects, the dependence of analysis algorithms and decision rules on the shooting conditions and image quality lead to the need to configure and retrain the computer vision system for al...
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ISBN:
(纸本)9783030500979
the infinite variety of image subjects, the dependence of analysis algorithms and decision rules on the shooting conditions and image quality lead to the need to configure and retrain the computer vision system for almost every next series of images. the paper proposes the principles of organization and high-level language for description of strategies of content-based analysis of aerospace images. the decision maker specifies the strategy for processing and analyzing the image as a sequence of points of selection of actions or subtasks. In general, each action can be performed by different software modules, which require their own data structures, restrictions and rules. Accordingly, the results of the action will vary. the solver, which is controlled by the given strategy, selects variants of actions, data and constraints for each subtask, builds a decision tree, and monitors the progress of the decision. Examples of object detection strategies and results of their work on urban area aerial images characterized by a very high spatial resolution are given. Applied semantic models of actions and resources make the process of structuring and describing more visual and, at the same time, machine-readable. the process of describing the image analysis strategy is transferred from the level of specifying instructions/commands to the level of planning works and resources.
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