Search Results - more ((((section algorithm) OR (selection algorithm))) OR (detection algorithm))

The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition by Othman, Mahmod, Syed Abdullah, Sharifah Lailee, Ahmad, Khairul Adilah, Abu Bakar, Mohd Nazari, Mansor, Ab Razak

“…To address this problem, this paper proposes a fusion of selected edge detection algorithms with mathematical morphology to enhance the ability to detect the object shape boundary. …”
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Face recognition using PZMI, ANN and Ant colony algorithms / Milad Miri by Milad , Miri

“…Usually, most of the standard face recognition systems contain four sections: face detection, feature extraction, feature selection, and classification. …”
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Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF) by Mazlan, Nurul Hidayah

“…This research synthesizes an evaluation of feature selection algorithm by utilizing Term Frequency-Inverse Document Frequency (TF-IDF) as the main algorithm in Android malware detection. …”
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Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm by Nikfal, Shima

“…To achieve such goal, this research modifies and improves the Reduction with Selective Redundancy (RSR) algorithm. In the modify algorithm, test cases would be selected according to the branch coverage if they covered different branch combination. …”
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Improving the efficiency of clustering algorithm for duplicates detection by Emran, Nurul Akmar, Abdul Rahim, Abdulrazzak Ali Mohamed, Kamal Baharin, Safiza Suhana, Othman, Zahriah, Salem, Awsan Thabet, Abd Aziz, Maslita, Md. Bohari, Nor Mas Aina, Abdullah, Noraswaliza

“…The more error-free the data, the more efficient the clustering algorithm, as data errors cause data to be placed in incorrect groups. …”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

“…In this paper, a new approach for Android botnet classification based on features selection and classification algorithms is proposed. …”
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Enhanced feature selections of Adaboost training for face detection using genetic algorithm (GABoost) by Mohd. Zin, Zalhan, Khalid, Marzuki, Yusof, Rubiyah

“…Generally, a large number of features are required to be selected for training purposes of face detection system. …”
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An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack by Yusof, Ahmad Riza’ain, Udzir, Nur Izura, Selamat, Ali

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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Some of the previous researchers used a feature set selection which is introduced for IDS but there still shortage in their detection rate and selected amounts of features. …”
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Tourist Trip Design Problem with user preference and popularity: a case study of Langkawi Island / Nabilah Anuar Ahmad and Huda Zuhrah Ab. Halim by Anuar Ahmad, Nabilah, Ab. Halim, Huda Zuhrah

“…The algorithm will choose POIs based on categories selected by the users. …”
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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm by Yab, Li Yu, Wahid, Noorhaniza, A. Hamid, Rahayu

“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). …”
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A detector generating algorithm for intrusion detection inspired by artificial immune system by Alsharafi, Walid Mohamed, Omar, Mohd Nizam

“…Artificial immune system (AIS) allows us to inspire several ideas for the design of computer intrusion detection.The standard of negative selection algorithm (NSA), offered by Stephanie Forrest in 1994, is one of the most common mechanisms in AIS that applied in anomaly detection for the similarity of its basic idea. …”
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Fault detection with optimum March test algorithm by Zakaria, Nor Azura, Wan Hassan, Wan Zuha, Abdul Halin, Izhal, Mohd Sidek, Roslina, Xiao, Qing Wen

“…The automation hardware was designed to give the flexibility to the user to generate other new March Algorithm prior to the selected algorithm and analyzed the performance in terms of fault detection and power consumption.…”
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Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A. Hamid, Rahayu

“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). …”
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Clonal selection algorithm for the cryptanalysis of a simple substitution cipher by Ahmad, Badrisham, Maarof, Mohd. Aizaini, Ibrahim, Subariah, Kutty Mammi, Hazinah, Mohamed Amin, Muhalim, Z'aba, Muhammad Reza

“…The development of Clonal Selection Algorithm (CSA) is inspired by elements from clonal selection theories. …”
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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat by Selamat, Nur Syuhada

“…The benefit of this work indicated that the implementation of a feature selection technique plays an important role in machine learning algorithms to increase the performance of detection.…”
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Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

“…These input features give information to the learning algorithms which used in intrusion detection system in the form of the detection method. …”
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Bot detection using machine learning algorithms on social media platforms by Gannarapu, Sainath, Dawoud, Ahmed, Ali, Rasha S., Alwan, Ali Amer

“…The components of the study are data, feature selection, and bot detection. The research performs web development and hosting on the collected data with a machine-learning algorithm to perform bot detection in social media networks. …”
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