Search Results - (( processes evaluation matching algorithm ) OR ( java simulation optimization algorithm ))
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1
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Thesis -
2
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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3
Evaluation of dynamic programming among the existing stereo matching algorithms
Published 2015“…There are various types of existing stereo matching algorithms on image processing which applied on stereo vision images to get better results of disparity depth map. …”
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4
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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5
Performance evaluation of automatic number plate recognition on android smartphone platform
Published 2017“…On the other hand, the traditional algorithm using template matching only obtained 83.7% recognition rate with 0.98 second processing time. …”
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Article -
6
GPU-based odd and even hybrid string matching algorithm
Published 2016“…String matching is considered as one of the fundamental problems in computer science.Many computer applications provide the string matching utility for their users, and how fast one or more occurrences of a given pattern can be found in a text plays a prominent role in their user satisfaction.Although numerous algorithms and methods are available to solve the string matching problem, the remarkable increase in the amount of data which is produced and stored by modern computational devices demands researchers to find much more efficient ways for dealing with this issue.In this research, the Odd and Even (OE) hybrid string matching algorithm is redesigned to be executed on the Graphics Processing Unit (GPU), which can be utilized to reduce the burden of compute-intensive operations from the Central Processing Unit (CPU).In fact, capabilities of the GPU as a massively parallel processor are employed to enhance the performance of the existing hybrid string matching algorithms.Different types of data are used to evaluate the impact of parallelization and implementation of both algorithms on the GPU. …”
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Conference or Workshop Item -
7
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
8
Instance matching framework for heterogeneous semantic web content over linked data environment
Published 2021“…The evaluation is performed on real-world datasets provided in different Ontology Alignment Evaluation Initiative (OAEI) campaign as benchmark data for instance matching track evaluation. …”
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9
Stereo matching algorithm based on hybrid convolutional neural network and directional intensity difference
Published 2021“…Fundamentally, a stereo matching algorithm produces a disparity map or depth map. …”
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10
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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Thesis -
11
Disparity map algorithm for stereo matching process using local based method
Published 2022“…The proposed SVDM algorithm involves four stages which starts from matching cost computation. …”
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12
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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13
A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm
Published 2021“…This paper presents a new composition of stereo vision algorithm for disparity map measurement from matching process. …”
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Article -
14
Disparity Refinement Process Based On Ransac Plane Fitting For Machine Vision Applications
Published 2017“…This paper presents a new disparity map refinement process for stereo matching algorithm and the refinement stage that will be implemented by partitioning the place or mask image and re-projected to the preliminary disparity images. …”
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15
Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction
Published 2019“…The experimental result on the proposed algorithm is able to reduce 17.4% of weighted average error for all and 9.62% of weighted average error for nonocc (nonoccluded) compared to others Stereo Matching Algorithm without the proposed framework. …”
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Thesis -
16
Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm
Published 2023Article -
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…To improve the UHDS16 algorithm, 8 × 8 block-matching technique has been tested. …”
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Book Chapter -
18
PRE AND POST PROCESSING APPROACHES FOR EFFICIENT FEATURE MATCHING PROCESS
Published 2014“…In this paper, the accuracy of SURF feature descriptors used in feature matching between two input images of extreme illumination levels are evaluated. …”
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19
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Book -
20
Image matching using relational graph representation
Published 2005“…Experiments are carried out to evaluate the applicability of incorporating structural information into the image matching algorithm. …”
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