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1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Article -
2
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Thesis -
3
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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4
Exploiting Features From Triangle Geometry For Digit Recognition
Published 2013“…Triangle is a basic geometry. There are six type of triangle, but scalene triangle was chosen to be used in this research that based on coordinates of corners generated by our proposed algorithm. …”
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Conference or Workshop Item -
5
An Optimized Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO) for cryptocurrency forecasting
Published 2019“…However, forecasting result using basic SVM algorithms does not really promising. …”
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Proceeding Paper -
6
Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. An enhancement version for kNN algorithm, k-General Nearest Neighbours (kGNN) have been proposed at initial stage. …”
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Monograph -
7
Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation
Published 2016“…Meanwhile, a set of descriptors corresponding to Elliptic Fourier Features shape description is extracted for each defect and is evaluated for each cluster to use for clustering and classification part. The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. …”
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8
Prediction Of Antimicrobial Peptides Based On Sequence Alignment And Secondary Structure Sequence And Segment Sequence.pdf
Published 2015“…This indicates that the proposed algorithm is not suitable to be used as AMPs predictor. …”
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9
FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES
Published 2013“…After analysis has been done, energy between Centromere and Nucleolar are different from each other and used to classify the pattern in SVM classifier. Tools used in this study are MATLAB software and image processing tools in MATLAB.…”
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Final Year Project -
10
Empirical study on intelligent android malware detection based on supervised machine learning
Published 2020“…More significantly, this paper empirically discusses and compares the performances of six supervised machine learning algorithms, known as K-Nearest Neighbors (K-NN), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), Naïve Bayes (NB), and Logistic Regression (LR), which are commonly used in the literature for detecting malware apps.…”
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Article -
11
Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks
Published 2024“…This scheme incorporates machine learning techniques by utilizing Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) classification algorithms to accurately identify and handle malicious network traffic following the initial packet filtration process that identifies abnormal traffic. …”
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12
Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…These ROIs were based on the training and the testing of the ANN, KNN, and SVM supervised machine-learning classifiers. Statistical measurements, such as the area under the receiver operating characteristic (ROC) curve (AUC), are used to evaluate classifier performance. …”
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