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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…The first algorithm locates interest points in food images using an MSER. …”
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An Optimized Semantic Segmentation Framework for Human Skin Detection by Huong, Audrey, Ngu, Xavier

“…The study incorporating optimization strategy in semantic segmentation is underexplored in dermatology. Existing approaches used complex and various heuristic designs of image processing algorithms and deep models customized for skin detection problems. …”
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New Algorithm of Location Model based on Robust Estimators and Smoothing Approach by Hamid, Hashibah

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A New Approach in a Gray-Level Image Contrast Enhancement by using Fuzzy Logic Technique by Hussain K., Khaleaf, Kamarul Hawari, Ghazali, Mithaq Na'ma, Raheema, Abdalla, Ahmed N.

“…In this paper, presenting a new approach to enhancing the image contrast by using fuzzy logic algorithm, so based on the fuzzy rule, we present a new membership equation, which represents the variable threshold level. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

“…WMH delineation on MRI images manually identified by experienced radiologists commonly uses visual score. However, the manual method is time-consuming, tedious, labour-intensive and inter-variability. …”
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Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES by MOHAMMAD SAMEER ALOUN

“…The unsupervised segmentation of color-texture regions using J-value segmentation (JSEG) algorithm is one of the most popular and robust unsupervised segmentation algorithms. …”
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

“…These algorithms have been applied to the problem of image segmentation. …”
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Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images by Farzan, Ali, Ramli, Abdul Rahman, Mashohor, Syamsiah, Mahmud, Rozi

“…Hence involving problem specific information and expert knowledge in designing segmentation algorithms seems to be useful. …”
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Enhanced Clustering Algorithms For Gray-Scale Image Segmentation by Siddiqui, Fasahat Ullah

“…The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy by Bhandari, A.K., Singh, V.K, Kumar, A., Singh, G.K.

“…A new approach of CS and WDO algorithm is used for selection of optimal threshold value. …”
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Multiregion segmentation of mammogram images by using parametric kernel graph cut algorithm / Nurhanani Abdul Rahim, Nor Farah Nabilah Mushtafa and Nadhirah Afiqah Zailan by Abdul Rahim, Nurhanani, Mushtaf, Nor Farah Nabilah, Zailan, Nadhirah Afiqah

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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The developed patterns are applied in the field of real-time analysis. Finally, the algorithm found, which would solve the image segmentation problem.…”
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Segmentation of Magnetic Resonance Brain Images Using Watershed Algorithm by Abdurrahim, Salem Hamed

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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm by Alomoush W., Alrosan A., Norwawi N., Alomari Y., Albashish D., Almomani A., Alqahtani M.