Search Results - (( based evaluation a algorithm ) OR ( label classification system algorithm ))

A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Abdullah F., Ahmad W.S.H.M.W.

Subjects: “…communication system…”

Extreme learning machine classification of file clusters for evaluating content-based feature vectors by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…The files are allocated in a continuous series of clusters. The ELM algorithm is applied to the DFRWS (2006) dataset and the results show that the combination of the three methods produces 93.46% classification accuracy.…”
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Classification of JPEG files by using extreme learning machine by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…This paper proposes an Extreme Learning Machine (ELM) algorithm to assign a class label of JPEG or Non-JPEG image for files in a continuous series of data clusters. …”
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad by Ahmad, Nurul Atirah

“…The system’s functionality based on the use case and usability tested by the Human Resources expert has been tested to evaluate its system requirements. …”
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Anomaly-based intrusion detection through K-means clustering and naives Bayes classification by Mohamed Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md. Nasir

“…Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification by Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md Nasir

“…Intrusion detection systems (IDSs) effectively balance extra security appliance by identifying intrusive activities on a computer system, and their enhancement is emerging at an unexpected rate.Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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A hierarchical deep convolutional neural network for asphalt pavement crack detection and classification / Nor Aizam Muhamed Yusof by Muhamed Yusof, Nor Aizam

“…The CrackLabel utilises a special design image thresholding algorithm known as Global and Lower Quartile Average Intensity (GLQAI). …”
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A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid by Saari, Mohamad Shahmil, Md Nor, Romiza, Huzaifah, A Hamid

“…By using image recognition, people can identify Harumanis feature details by image recognition technique where algorithm is applied to recognize the mango. Convolutional neural networks method is a suitable technique for the creation of a multi-fruit in real-time classification sorter with the camera and for the detection of moving fruit. …”
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Flow-based approach on bro intrusion detection by Alaidaros, Hashem, Mahmuddin, Massudi

“…Bro was used to generate malicious features from several recent labeled datasets. Then, the model made use the machine learning classification algorithms for attribute evaluation and Bro policy scripts for detecting malicious flows. …”
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Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm by Dhewa, Oktaf Agni, Utama, Safitri Yuliana, Nasuha, Aris, Gunawan, Teddy Surya, Pratama, Gilang Nugraha Putu

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Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

“…The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.…”
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Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer�s Disease by Sadiq, A., Yahya, N., Tang, T.B., Hashim, H., Naseem, I.

“…From this matrix, significant connections evaluated using the p-value are selected as an input to a classifier for the classification of Alzheimerâ��s vs. normal controls. …”
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Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz by Abd Aziz, Nur Hasyimah

“…CNN was chosen as an algorithm for classification task because various studies had concluded that it is able to produce highly accurate result. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…Seven machine learning models—Artificial Neural Network (ANN), Random Forest (RF), Decision Tree (DTT), k-Nearest Neighbors (k-NN), Naïve Bayes (NB), Support Vector Machine (SVM), and Deep Neural Network (DNN)—were used for multi-label classification of the complications. The study employed two MLC frameworks: Problem Transformation methods (Binary Relevance, Classifier Chains, Label Power Set, and Calibrated Label Ranking) and Algorithm Adaptation. …”
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VEHICLE CLASSIFICATION USING NEURAL NETWORKS AND IMAGE PROCESSING by ONG KANG WEI, ONG KANG WEI, LOH SER LEE, LOH SER LEE

“…The aim of this study is to propose a vehicle classification scheme where YOLO v5 algorithm and Faster R-CNN algorithm are being implemented separately into vehicle classification, followed by comparison of result between these two algorithms. …”
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Diagnostic And Classification System For Kids With Learning Disabilities by Rehman, Ullah Khan, Julia Ai Cheng, Lee, Yin, Bee Oon

“…In this research, we propose an automated diagnostic and classification system. The system is trained by pre-classified data of 857 school children scores in spelling and reading. …”
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Transformer-Based Model for Malicious URL Classification by Do N.Q., Selamat A., Lim K.C., Krejcar O., Ghani N.A.M.

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Anomaly detection in ICS datasets with machine learning algorithms by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Abdul Rahman, Farah Diyana, Tahir, Mohammad

“…The machine learning algorithms have been performed with labeled output for prediction classification. …”
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Content-based feature selection for music genre classification by Muda, Noor Azilah, Choo, Yun Huoy, Norashikin, Ahmad

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