Search Results - (( based evaluation swarm algorithm ) OR ( image classification _ algorithm ))

Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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Optimized image enhancement of colour processing for retinal fundus image by Nurul Atikah, Mohd Sharif

“…Tests on 600 retinal fundus images from primary and secondary datasets were performed to benchmark the algorithm two existing approaches. …”
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Optimized image enhancement of colour processing for retinal fundus image by Nurul Atikah, Mohd Sharif

“…Tests on 600 retinal fundus images from primary and secondary datasets were performed to benchmark the algorithm two existing approaches. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…This process consists of four steps: pre-processing, segmentation, feature extraction, and classification. In this research, we evaluate proposed algorithms on two datasets, International Skin Imaging Collaboration (ISIC) and PH2 (Dermatology Service of Hospital Pedro Hispano, Matosinhos, Portugal). …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Recently, various techniques based on different algorithms have been developed. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

“…Based on the final denoised images, the model has proven its reliability, in terms of both visual quality and quantitative evaluation. …”
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Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Mohd Falfazli, Mat Jusof, Kian, Sheng Lim

“…Multi Objective Optimisation (MOO) problem involves simultaneous minimization or maximization of many objective functions. One of MOO algorithms is Vector Evaluated Particle Swarm Optimization (VEPSO) algorithm. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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Improved particle swarm optimization by fast annealing algorithm by Bashath, Samar, Ismail, Amelia Ritahani

“…To evaluate its performance, we examined the algorithm on 14 benchmark functions. …”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

“…The review is based on how the algorithms deal with objective functions using MOO approaches, the benchmark MOPs used in the evaluation and performance metrics. …”
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Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri

“…Their performance is evaluated and compared based on seven performance criteria. …”
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Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

“…This paper has evaluated the immune algorithm in 12 common benchmark dataset to evaluate the performance of rough reducts-based on attribute reduction. …”
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Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization by Zuwairie, Ibrahim, Mohamad Nizam, Aliman, Fardila, Naim, Sophan Wahyudi, Nawawi, Shahdan, Sudin

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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

“…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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Evaluation Algorithm - Based on PID Controller Design for the Unstable Systems by Wan Ismail, Ibrahim, Erliza, Serri, Mohd Riduwan, Ghazali

“…In this project, the evaluating PSO algorithm based on PID controller design for unstable system was proposed. …”
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Levy tunicate swarm algorithm for solving numerical and real-world optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

“…The proposed Levy Tunicate Swarm Algorithm (LTSA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic algorithm called Tunicate Swarm Algorithm (TSA) to solve numerical and real-world optimization problems. …”
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An Improved Multi-State Particle Swarm Optimization for Discrete Optimization Problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

“…Recently, a state-based algorithm called multi-state particle swarm optimization (MSPSO) has been proposed to solve discrete combinatorial optimization problems. …”
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Document clustering based on firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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