Search Results - (( developing matrix classification algorithm ) OR ( java application based algorithm ))

Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun by Mohammad Harun, Muhammad Firdaus

“…The algorithm were used to perform the supervised classification. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING NEIGHBORHOOD GREY TONE DIFFERENT MATRIX METHOD by JAMALUDIN, NORHIDAYAH

“…Thus, three types of texture selected, which consist of thirty images respectively, are analyzed using the algorithm of first and second order statistic developed in MATLAB. …”
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Development of interactive application for classification of Artocarpus Species by Abdul Ghapar, Nadia

“…Support Vector Machine (SVM) will be used to get the highest accuracy for the classification of Artocarpus species. The combination of Prewitt algorithm, Canny alogorithm, Gray-Level co-occurrence matrix will be used in SVM. …”
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IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH by MOHD YAKOP, SITI HAJAR

“…The objective of this project is to develop algorithms inMATLAB and be able to implement image texture analysis by using the developed algorithms. …”
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Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

“…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

“…This research will be conducted by using digital image processing approach based on the morphological features of leaf with the combination of gray level co-occurrence matrix (GLCM), Prewitt and Canny algorithm and training classification models by using support vector machine (SVM). …”
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Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
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Lightning fault classification for transmission line using support vector machine by Asman, Saidatul Habsah, Ab Aziz, Nur Fadilah, Ab Kadir, Mohd Zainal Abidin, Ungku Amirulddin, Ungku Anisa, Roslan, Nurzanariah, Elsanabary, Ahmed

“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. The classification performance of the developed algorithms was evaluated using confusion matrix. …”
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Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

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Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm by Taman, Ishak, Md Rosid, Nur Atika, Karis, Mohd Safirin, Hasim, Saipol Hadi, Zainal Abidin, Amar Faiz, Nordin, Nur Anis, Omar, Norhaizat, Jaafar, Hazriq Izzuan, Ab Ghani, Zailani, Hassan, Jefery

“…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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A review on classifying and prioritizing user review-based software requirements by Salleh, Amran, Said, Mar Yah, Osman, Mohd Hafeez, Hassan, Sa’Adah

“…Investigating the potential of emerging machine learning models and algorithms to improve classification and prioritization accuracy is crucial. …”
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Classification of brain tumors: using deep transfer learning by Husin, Nor Azura, Husam, Mohamed, Hussin, Masnida

“…Brain tumor classification is important for diagnosing and treating cancers. …”
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Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

“…The methodology starts with literature comprehension studies on the computation pitfalls and existed augmentation studies of Simplex algorithm. Then, followed by concept development which consists of concept extraction, computation stages classification and algorithms integration. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Personality prediction using Random Forest algorithm / Wan Abdul Qayyum Abdul Wahab by Abdul Wahab, Wan Abdul Qayyum

“…The output of this project included the project's conceptual framework, system architecture, user interface, and performance assessment, such as the confusion matrix and accuracy computation. The conclusion emphasized the findings' relevance in improving knowledge of personality prediction and classification systems, as well as future project upgrade ideas.…”
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Novel Feature Extraction and Representation for Currency Classification by Wang, Hui Hui, Wang, Yin Chai, Wee, Bui Lin, Marcus, Chen

“…The highest similarity percentage will be chosen as the currency's origin. The proposed algorithm successfully classified the currency and improved the accuracy of currency classification, achieving a 93.4% accuracy rate from the experimental results. …”
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