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Parallel Algorithm for Hardware Implementation of Inverse Halftoning
Published 2005“…The algorithm is based on Lookup Tables from which the inverse halftone value of a pixel is directly determined using a pattern of pixels. …”
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163
Parallel algorithm for hardware implementation of inverse halftoning
Published 2005“…The algorithm is based on lookup tables from which the inverse halftone value of a pixel is directly determined using a pattern of pixels. …”
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164
Mapping realistic data sets on parallel computers
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conferenceObject -
165
Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests
Published 2023“…This paper describes how trial-based dominance can totally order this two-variable dataset of outcomes so that traditional non-parametric methods can determine the better of two algorithms when one is faster, but less accurate than the other, i.e. when neither algorithm dominates. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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168
Implementation of trust region methods in optimization. (c1998)
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masterThesis -
169
Sentiment visualization of correlation of loneliness mapped through social intelligence analysis
Published 2024“…Social media platforms have become a valuable source of data to study this phenomenon.</p><h3>Objectives</h3><p dir="ltr">This paper aims to visualize the frequency of loneliness-related themes and topics in Twitter data. …”
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170
Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…Whilst different models are proposed for STLF, they are based on small historical datasets and are not scalable to process large amounts of big data as energy consumption data grow exponentially in large electric distribution networks. …”
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171
Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems
Published 2023“…The last retained features from the proposed PSO-based methods are fed to the neural network (NN) classifier. …”
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172
Machine Learning Model for a Sustainable Drilling Process
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173
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174
Data redundancy management for leaf-edges in connected environments
Published 2022“…Major advances in the fields of Internet and Communication Technology (ICT), data modeling/processing, and sensing technology have rendered traditional environments (e.g., cities, buildings) more connected. …”
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175
Recent Advances of Chimp Optimization Algorithm: Variants and Applications
Published 2023“…Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. …”
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176
Data reductions and combinatorial bounds for improved approximation algorithms
Published 2016“…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …”
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177
A novel linear time corner detection algorithm
Published 2005“…We have presented a novel scheme for detecting corners of a planner object SRM05. The core of the algorithm is based upon slope analysis. The complexity of our algorithm is linear. …”
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178
A neural networks algorithm for data path synthesis
Published 2003“…The algorithm is driven by a motion equation that determines the neurons firing conditions based on the modified Hopfield neural network model of computation. …”
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179
A direct algorithm for the parameterized face cover problem
Published 2017“…Recent improvements to face cover algorithms are based on the theory of fixed-parameter tractability and reductions to planar dominating set. …”
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conferenceObject -
180
A hybrid graph representation for recursive backtracking algorithms
Published 2017“…The performance of these algorithms often suffers from the increasing number of graph modifications, such as deletions, that reduce the problem instance and have to be “taken back” frequently during the search process. …”
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