Search Results - (( form detection method algorithm ) OR ( java application learning algorithm ))

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    Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

    Published 2018
    “…TVS algorithm design is still challenging because most of the recent methods are unable to achieve robust detection for different types of transitions: hard transition (HT) and soft transition (ST). …”
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    A Detection Method for Text Steganalysis Using Evolution Algorithm (EA) Approach by Puriwat, Lertkrai

    Published 2012
    “…Therefore, this research employed a detection factor based on the evolution algorithm method for text steganalysis. …”
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    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    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

    Published 2016
    “…Implementation of the proposed method shows that it is robust and applicable for various kind of fruit images and is more accurate than the existing edge detection algorithms.…”
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    Single-linkage method to detect multiple outliers with different outlier scenarios in circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Roslinazairimah, Zakaria

    Published 2018
    “…Single-linkage is one of the algorithms in agglomerative clustering technique that can be used to detect outliers. …”
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    Comparison on machine learning algorithm to fast detection of malicious web pages by Wan Nurul Safawati, Wan Manan, Mohd Nizam, Mohmad Kahar, Noorlin, Mohd Ali

    Published 2021
    “…Furthermore, previous approached have used blacklist technique which a conventional method and have shown promising result in detecting malicious webpages. …”
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    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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    Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

    Published 2016
    “…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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    An integrated deep learning deepfakes detection method (IDL-DDM) by Yassin, Warusia, Johan, Azwan, Abas, Zuraida Abal, Baharon, Mohd Rizuan, Bejuri, Wan, Ismail, Anuar

    Published 2024
    “…Nevertheless, various detection methods for deepfakes have been schemed, and the accuracy of such detection models still emerges as an open issue, particularly for research communities. …”
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    Wormhole attack detection mechanism in mobile ad hoc network using neighborhood information and path tracing algorithm by Enshaei, Mehdi

    Published 2015
    “…Path Tracing (PT) Algorithm was proposed to detect and prevent exposed wormhole attacks in MANET. …”
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    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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    Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

    Published 2016
    “…A unique method that combines the Flexible Packet Filtering (FPF) with Support Vector Machine (SVM) algorithm is proposed to classify the behavior of the network traffics. …”
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    Heartbeat Anomaly Detection Method Based on Electrocardiogram using Improved Certainty Cognitive Map by Sumiati, .

    Published 2023
    “…This research has 3 objectives To develop algorithms for detecting heart conditions as either abnormal or normal using the modified cognitive map (CM) approach, To develop detection algorithms for anomalous heart conditions based on the enhancement of Certainty Factor (CF) technique, and To evaluate and validate the effectiveness of the new proposed model specifically the Certainty Cognitive Map (CCM) for identifying heart defects. …”
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    Failure detection analysis of grid-connected photovoltaic system using an improved comparative based method / Fatin Azirah Mohd Shukor by Mohd Shukor, Fatin Azirah

    Published 2022
    “…In order to gain feasible economic return, failure detection (FD) mechanisms are given utmost attention to monitor the performance and yet able to detect fault occurrence of the operating GCPV system especially in the form of analysis algorithm. …”
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    An Enhanced Mechanism To Detect Drdos Attacks On Dns Using Adaptive Thresholding Technique by Al Ogaili, Riyadh Rahef Nuiaa

    Published 2023
    “…As a result, traditional mechanisms are incapable of detecting these types of cyberattacks. As a result, existing detection mechanisms are unable to detect these forms of cyber intrusions. …”
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