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Model selection approaches of water quality index data
Published 2016“…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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Power System State Estimation In Large-Scale Networks
Published 2010“…The Weighted Least Squares (WLS) method is the most popular technique of SE. This thesis provides solutions to enhance the WLS algorithm in order to increase the performance of SE. …”
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Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)
Published 2021“…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025“…The new DFGPSO algorithm is specifically designed to address the intrinsic challenges in PV modelling, such as local optima entrapment and slow convergence rates that typically hinder traditional optimization methods. …”
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Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…Those algorithms which performed estimation carrying out lots of calculation that leads in expensive methods in terms of computing resources. …”
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GMSD-based perceptually motivated non-local means filter for image denoising
Published 2019“…The overall process is broken down into two steps; initially, local noise estimates for the underlying noisy patch are approximated and removed, then the refined patch is fed to the weighting process as the final step. …”
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Towards a unified image quality assessment technique for cross-content image processing applications
Published 2024“…The study’s second objective is to apply IQA practically in image processing applications/operations. It specifically tackles image reconstruction, a vital post-processing task in image systems. …”
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Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images
Published 2018“…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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Photogrammetric unmanned aerial vehicle for digital terrain model estimation under oil palm tree canopy area / Suzanah Abdullah
Published 2021“…At this stage, this study has formulated a new methodology for estimating DTM production under tree canopy conditions based on tree crown estimation produced from the digital surface model (DSM) and subsequently, the tree height estimation was determined as the final process in the DTM implementation. …”
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Image-based Ananas Comosus detection and counting using artificial neural network / Wan Nurazwin Syazwani Rahimi
Published 2021“…Therefore, to automate the process of fruit detection, counting, and yield estimation, a two-step process, namely image processing and artificial neural network (ANN), was proposed. …”
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Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation
Published 2013“…This algorithm, which is term triangular cross-observation (TCO), involves three mobile robots simultaneously in every update decision making process, which provides two observation data for every robot. …”
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Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm
Published 2022“…In addition, a method of utilizing Convolutional Neural Network (CNN) is used for the detection of vehicles from roadway camera outputs to apply video processing techniques and extract the desired information. …”
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Enhanced Reinforcement Learning Model for Extraction of Objects in Complex Imaging
Published 2022“…The effects of image segmentation have an effect on the image processing process. In general, it includes the description and specification of objects; higher order tasks follow, such as entity classification and attribute estimation. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Based on previous researches, most existing segmentation methods focused on a specific environment. Therefore, this research has developed an improved edge detection and contour segmentation algorithm that is able to correctly segment various objects from both indoor and outdoor images. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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Covariance matrix analysis in simultaneous localization and mapping
Published 2016“…Estimation at a specific time or also known as the filtering technique in estimation and control theory is a method to estimate the desired parameters from indirect and uncertain observations, taking into account the system and measurement errors. …”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia
Published 2015“…In this study, several algorithms are proposed to guarantee high efficiency of resource allocations among a variety of smart grid applications (flat priority based and specific priority based scheduling algorithms), such as distribution automation, voice, video surveillance and advanced metering infrastructure. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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