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Enhanced Clustering Algorithms For Gray-Scale Image Segmentation
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A New Approach in a Gray-Level Image Contrast Enhancement by using Fuzzy Logic Technique
Published 2015“…Fuzzy Logic technique represents a new approach for gray level image contrast enhancement. The image contrast problem is one of the main problems that confront the researchers in the field of digital image processing, such as in the biomedical image processing like X-Ray and MRI image segmentation for disease classification. …”
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Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm
Published 2023“…These values can be benchmarked in solving multi-objective GMS problems using the multi-objective PACS algorithm and its variants.…”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images
Published 2010“…Due to some properties of MR images such as intensity inhomogeneity of tissues, partial volume effect, noise and some other imaging artifacts, segmentation of brain MRI based on voxel gray values is prone to error. Hence involving problem specific information and expert knowledge in designing segmentation algorithms seems to be useful. …”
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Predictive Analytics in Genetic Engineering as an Optimization Problem
Published 2024“…The nature of the problem requires that a stochastic optimization algorithm be applied in the metaheuristic search rather than using a deterministic or mathematical approach. …”
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Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…The basic feature extraction of minimum, maximum and mean of gray level values are used as the parameter to develop the prototype. …”
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11
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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A Hybrid Ant-Wolf Algorithm to Optimize Assembly Sequence Planning Problem
Published 2017“…Purpose – This paper aims to optimize the assembly sequence planning (ASP) problem using a proposed hybrid algorithm based on Ant Colony Optimization (ACO) and Gray Wolf Optimizer (GWO). …”
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Ant colony optimization algorithm for load balancing in grid computing
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation
Published 2022“…The comparative optimization algorithms include two BWOA variants, binary bat algorithm (BBA), binary gray wolf algorithm (BGWOA), and binary manta-ray foraging algorithm (BMRFO). …”
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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19
Face Detection System / Chan Beh Teng
Published 2004“…Skin regions are then separated from skin regions by segmenting the gray-scale image. After that, the system will locate the frontal human face(s) within the skin regions, using template matching. …”
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20
Micro-Crack Detection Of Solar Cells Featuring Adaptive Anisotropic Diffusion Filter And Semi-Supervised Support Vector Learning
Published 2014“…Nevertheless, the micro-crack defect exhibits some unique properties such as high in gradient and low gray-levels. These properties together with the shape feature of the micro-crack are used in developing the detection algorithm. …”
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