Search Results - (( java application based algorithm ) OR ( basic detection (matching OR machine) algorithm ))

Steg Analysis Algorithm for Edge Adaptive Least Significant Bit Matching Revisited Detection by Edris, Khalid Edris, Fakhreldin, Mohammed Adam Ibrahim, Jasni, Mohamad Zain, Tuty Asmawaty, Abdul Kadir

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Enhancement of network security by use machine learning by Hasan, Ahmed Raheem

“…The ANNDL uses iterations method to detect the data, do matching and identify the data. …”
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Disparity Refinement Based on Depth Image Layers Separation for Stereo Matching Algorithms by Abd Manap, Nurulfajar, Soraghan, John J.

“…This paper presents a method to improve the raw disparity maps in the disparity refinement stage for stereo matching algorithm. The proposed algorithm will use the disparity depth map from the stereo matching algorithm as initial disparity depth output with a basic similarity metric of SAD. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

“…As network attackers keep changing their methods of attack execution to evade the deployed intrusion-detection systems (IDS), machine learning (ML) algorithms have been introduced to boost the performance of the IDS. …”
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Segmentation of Malay syllables in connected digit speech using statistical approach by Salam, M.S., Mohamad, Dzulkifli, Saleh, S.H.

“…Segmentation was done in time domain signal using statistical approaches namely the Brandt’s Generalized Likelihood Ratio (GLR) algorithm and Divergence algorithm. These approaches basically detect abrupt changes of energy signal in order to determine the segmentation points. …”
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A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system by M.H., Ali, Mohamad, Fadlizolkipi, Ahmad Firdaus, Zainal Abidin, Nik Zulkarnaen, Khidzir

“…Hybrid model's approaches have been widely used to increase the effectiveness of intrusion-detection platforms. This work proposes the extreme learning machine (ELM) is one of the poplar machine learning algorithms which, easy to implement with excellent learning performance characteristics. …”
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A comparative analysis of image copy-move forgery detection algorithms based on hand and machine-crafted features by Ahmed I.T., Hammad B.T., Jamil N.

“…IC-MFDs based hand-crafted features and IC-MFDs based machine-crafted features. IC-MFD algorithms based hand-crafted features are the algorithms that detect the faked image depending on manual feature extraction while IC-MFD algorithms based machine-crafted features are the algorithms that detect the faked image automatically from image. …”

Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
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Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review by Mat Ripah N.A., Abdul Latif A., Che Cob Z., Mohd Drus S., Md Anwar R., Mohd Radzi H.

“…Furthermore, it is also shown that various machine learning algorithms are used, and the most used are Neural Network and Support Vector Machine. …”

Investigate And Analysis Of Deep Learning And Machine Learning Algorithm For Face Mask Detection System by Muhammad Ezzuddeen, Suratman

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Face Detection System / Chan Beh Teng by Chan, Beh Teng

“…The method used for detecting face is a combination of color based technique and template matching. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Shot boundary detection based on orthogonal polynomial by Abdulhussain, Sadiq H., Ramli, Abd Rahman, Mahmmod, Basheera M., Saripan, Mohd Iqbal, Al-Haddad, Syed Abdul Rahman, Jassim, Wissam A.

“…Finally, the support vector machine is utilized to detect hard transitions. In addition, a comparison between the proposed algorithm and other state-of-the-art algorithms is performed to reinforce the capability of the proposed work. …”
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Cars detection in stitched image using morphological approach by Joselyn, Jok.

“…The performance of the proposed cars detection algorithm could detect the cars fairly accurate. …”
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A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features by Keshkeh, Kinan, Jantan, Aman, Alieyan, Kamal

“…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. …”
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The development of virtual product life cycle design tool using artificial intelligence technique by Harun, Habibollah, Ismail @ Ishak, Hasrul Haidar, Sukimin, Zuraini

“…The generated features from code classification algorithm give the information of machining parameter through the mapping algorithm. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer by Tehseen Mazhar, Inayatul Haq, Allah Ditta, Syed Agha Hassnain Mohsan, Faisal Rehman, Imran Zafar, Jualang Azlan Gansau, Lucky Poh Wah Goh

“…Moreover, this paper also defined the basic requirements for creating a skin cancer detection application, which revolves around two main issues: the full segmentation image and the tracking of the lesion on the skin using deep learning. …”
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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

“…Furthermore, a comprehensive review of the existing static, dynamic, and hybrid Android malware detection approaches is presented in this study. 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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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

“…This isolation is essentially a classification task, which led researchers to attempt the application of well-known classifiers from the area of machine learning to intrusion detection. Neural Networks (NNs) are one of the most popular techniques to perform non-linear classification, and have been extensively used in the literature to perform intrusion detection. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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