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1
Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications
Published 2016“…DSF algorithm is a hybrid stereo matching algorithm which divided into two phases. …”
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Thesis -
2
Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Recently, intelligent searching methods were proposed to enhance the computational optimization issues in motion estimation but still lack in obtaining the best solution of block matching. …”
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3
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. …”
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4
Stereo matching algorithm using census transform and segment tree for depth estimation
Published 2023“…This article proposes an algorithm for stereo matching corresponding process that will be used in many applications such as augmented reality, autonomous vehicle navigation and surface reconstruction. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Genetic Algorithms are very efficient at exploring the entire search space; however, they are relatively poor at finding the precise local optimal solution in the region at which the algorithm converges. …”
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A fuzzy case-based reasoning model for software requirements specifications quality assessment
Published 2023“…Additionally, for efficient cases retrieval in the CBR, relevant cases selection and nearest cases selection heuristic search algorithms are used in the system. Basically, the input to the relevant cases algorithm is the available cases in the system case base and the output is the relevant cases. …”
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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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Assessment of cognitive load using multimedia learning and resting states with deep learning perspective
Published 2019“…The brain waves were extracted using discrete wavelet transform (DWT) for each segment and fed these segments to proposed model for classification and assessment of cognitive load. The results shows that alpha brain wave produced consistent behavior using for all cognition tasks based on pre-trained CNN models for classification and cognitive load assessment. …”
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Review of Plug-Based Load Energy Management Systems (PLEMS) for energy and comfort management of buildings
Published 2016“…The reviews indicate that it is essential to improve plug-based load equipments efficiency standards. Classification of these electrical devices according to their consumption patterns would facilitate energy wastage analysis and predictions of future consumption patterns. …”
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Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System
Published 2019“…This model implements Non-Recursive Phasor Estimation (NRPE) algorithm. Secondly, the study proposes an index for faulty node classification (FNC) based on the positive sequence voltage (PSV) measurements of the pre-fault and post-fault conditions. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…The EFDT and hybrid DT-SVM algorithms were designed and deployed based on DT and SVM algorithms to achieve improved performance. …”
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An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa
Published 2018“…Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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An application of a novel technique for assessing the operating performance of existing cooling systems on a university campus
Published 2018“…Then, the algorithm-based classifier APSO has better results compared to the conventional particle swarm optimization (PSO). …”
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Dynamic load balancing policy in grid computing with multi-agent system integration
Published 2011“…The policy in dynamic load balancing, classification and function are variety based on the focus study for each research. …”
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High impedance fault detection and identification based on pattern recognition of phase displacement computation
Published 2018“…Subsequently, an automatic HIF classification algorithm based on predefined indices is proposed to perform event identification and HIF detection. …”
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Service based load balance mechanism using software-defined networks / Ahmed Abdelaziz Abdelltif Osman
Published 2017“…To address aforementioned problems, we proposed a service based load balance (SBLB) mechanism using Software-Defined Networks (SDN). …”
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Scalable Self-Organizing Model for Grid Resource Discovery
Published 2008“…The paper also proposes a resource discovery algorithm that optimizes resource query on the Grid network. …”
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Power system security assessment using artificial neural network: article / Mohd Fathi Zakaria
Published 2010“…Extensive testing and training of the proposed ANN based apprnach indicates its viability for power system steady state stability classification assessment.…”
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Dynamic load balancing policy with communication and computation elements in grid computing with multi-agent system integration
Published 2011“…The policy in dynamic load balancing, classification and function are variety based on the focus study for each research. …”
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