Search Results - processes evaluation ((method algorithm) OR (based algorithm))
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Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods
Published 2021“…In addition, the weight of importance is critical for evaluating the performance of MaOO algorithms. All evaluation studies for MaOO algorithms have ignored to assign such weight for the target criteria during evaluation process. …”
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2
Sudoku Generator based on hybrid algorithm / Faridah Abdul Rahman
Published 2012“…After testing and evaluation the prototype, the result shows that the Sudoku generator based on hybrid algorithm takes more times on solving the Sudoku. …”
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Evaluation of dynamic programming among the existing stereo matching algorithms
Published 2015“…The dynamic programming algorithm used on this research is the current method as its disparity estimates at a particular pixel and all the other pixels unlike the old methods which with scanline based of dynamic programming. …”
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Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images
Published 2012“…The algorithm was written by using MATLAB software. The local tone mapping method is based on the modified contrast limited adaptive histogram equalization (CLAHE) method. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Evaluation was made based on various evaluation metrics related to outlier detection and clustering quality. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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Literature Survey On Stereo Vision Disparity Map Algorithms
Published 2016“…The survey also notes the implementation of previous software-based and hardware-based algorithms. Generally, the main processing module for a software-based implementation uses only a central processing unit. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications
Published 2016“…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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Disparity map algorithm for stereo matching process using local based method
Published 2022“…Hence, this thesis proposes a local-based SVDM algorithm that increases the accuracy on the complex scenes. …”
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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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12
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…If the feature extraction process fails to capture the correct information, the performance or accuracy of the classification algorithm will be negatively impacted. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…System identification is a method of determining a mathematical relation between variables and terms of a process based on observed input-output data. …”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…To evaluate the performance of the proposed IBOA training method, the obtained results are compared to the results of the momentum backpropagation (MBP), the particle swarm optimization (PSO) and the standard butterfly optimization algorithm (BOA) training methods. …”
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article -
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…To evaluate the performance of the developed algorithm, the average PSNR value, average search point and average elapsed processing time is calculated. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis meth...
Published 2020“…Given the rapid development of dehazing image algorithms, selecting the optimal algorithm based on multiple criteria is crucial in determining the efficiency of an algorithm. …”
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Stereo matching algorithm based on hybrid convolutional neural network and directional intensity difference
Published 2021“…The proposed algorithm contains a deep learning-based method and a handcrafted method. …”
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