Search Results - (( java segmentation using algorithm ) OR ( basic learning svm algorithm ))

Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Exploiting Features From Triangle Geometry For Digit Recognition by Azmi, Mohd Sanusi, Nasrudin, Mohammad Faidzul, Omar, Khairuddin, Che Wan Ahmad, Che Wan Shamsul Bahri, Wan Mohd Ghazali, Khadijah

“…Experiments will be conducted using supervised learning that are Support Vector Machine (SVM) and Multi-layer Perceptron (MLP). …”
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Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

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An Optimized Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO) for cryptocurrency forecasting by Hitam, Nor Azizah, Ismail, Amelia Ritahani, Saeed, Faisal

“…Some may use Machine Learning Algorithms to execute their trades. However, forecasting result using basic SVM algorithms does not really promising. …”
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

“…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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Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

“…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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Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks by Najmun, Najmun

“…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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Real-time oil palm fruit bunch ripeness grading system using image processing techniques by Alfatni, Meftah Salem M.

“…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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