Search Results - (( based segmentation using algorithm ) OR ( using vectorization machine 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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Micro-Crack Detection Of Solar Cells Featuring Adaptive Anisotropic Diffusion Filter And Semi-Supervised Support Vector Learning by Majid, Said Amirul Anwar B Ab Hamid @ Ab

“…These properties together with the shape feature of the micro-crack are used in developing the detection algorithm. In this work, an image processing algorithm featuring an adaptive anisotropic diffusion filter and a segmentation technique based on twostage thresholding is proposed. …”
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Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

“…In the first part of the proposed algorithm, unique moments coefficients (features) are extracted using a new hybrid set of orthogonal polynomials which is derived based on the modified forms of Krawtchouk and a Tchebichef polynomials. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…For segmentation, the first proposed algorithm is based on the boundary condition model, which is tested over the ISIC dataset and achieved 96% of accuracy. …”
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Fast temporal video segmentation based on Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H., Al-Haddad, Syed Abdul Rahman, Saripan, M. Iqbal, Mahmood, Basheera M., Hussien, Aseel

“…This utilization will lead to extract multiple local features with low computational cost. Support vector machine (SVM) classifier is used to detect transitions. …”
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Fast shot boundary detection based on separable moments and support vector machine by Idan, Zinah N., Abdulhussain, Sadiq H., Mahmmod, Basheera M., Al-Utaibi, Khaled A., Syed Abdul Rahman Al-, Syed Abdul Rahman Al-Hadad, Sait, Sadiq M.

“…As a result, the computational cost is reduced in the subsequent stages. Finally, machine learning statistics based on the support vector machine is implemented to detect the cut transitions. …”
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Classification red blood cells using support vector machine by Akrimi J.A., Suliman A., George L.E., Ahmad A.R.

Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

“…Comparisons were made between the proposed method to the k-nearest neighbor (KNN) and support vector machine (SVM), methods for image segmentation. …”
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Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

“…In order to obtain a good classification accuracy, the suitable segmentation parameters (scale, shape and compactness) and features selection have been determined and Machine learning (ML) algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT) classifiers have been applied to categorized five different classes which are water, forest, green area, building, and road. …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…The quality of the interest region detector was evaluated based on the quantity of interest regions. Classification was performed using a Support Vector Machine (SVM) with a linear kernel. …”
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Improving Brain MR Image Classification for Tumor Segmentation using Phase Congruency by Ghazanfar, Latif, Dayang Nur Fatimah, Binti Awg Iskandar, Jaafar, Alghazo, Arfan, Jaffar

“…Aims: This research aims to improve automated brain MR image classification and tumor segmentation using phase congruency. Methods: The skull part is removed from brain MR image by applying converging square algorithm and phase congruency based edge detection method. …”
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Simple realization of 5-Segment discontinuous SVPWM based on FPGA by Sutikno, Tole, Jidin, Auzani, Basar, Mohd Farriz

“…Unfortunately, the modulation algorithm is mainly implemented with software based on microcontroller or digital signal processors (DSP). …”
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A Comparative Performance Analysis of Malware Detection Algorithms Based on Various Texture Features and Classifiers by Ahmed I.T., Hammad B.T., Jamil N.

Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab by Wahhab, Hayan Tareq Abdul

“…Artificial Neural Network and Support Vector Machine were used to classify blast cells into either ALL or AML according to the extracted features. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image by Shojanoori, Razieh

“…This study also explores the use and comparison of object-based classification, and two common pixel-based classification methods namely, maximum likelihood and support vector machines based on WorldView-2 satellite imagery to evaluate the potential of the object-based in compare to pixel-based to detect urban tree species. …”
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Development of sorting system for oil palm in vitro shoots using machine vision approach by Al-Ruhaimi, Hamdan Yahya Ahmed

“…Ultimately, the sorting algorithm performance came to be evaluated by support vector machine algorithm. …”
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Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection by Chyntia Jaby, Entuni

“…Some of the existing methods of segmentation are K-Means, Otsu’s, edge-based segmentation, watershed segmentation, region growing, mean shift, maxflow mincut (MFMC) graph cut and regional colour segmentation. …”
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Visualization on colour based flow vector of thermal image for movement detection during interactive session by Ibrahim, Nabilah, Raman, Mohamad Nurazmi, Mahadi, Lina Farhana, Wan Zakaria, Wan Nurshazwani

“…The results obtained could be observed in flow vector parameter and the segmentation colour based image for the time frame from 1 to 10 seconds. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…The methodology is proposed as stacking ensemble ML and the best ML algorithms are used as a base learner to compute relative feature weights. …”
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