Search Results - (( basic detection machine algorithm ) OR ( using optimization method algorithm ))
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1
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…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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2
Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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Thesis -
3
A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system
Published 2018“…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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4
A comparative analysis of image copy-move forgery detection algorithms based on hand and machine-crafted features
Published 2023“…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. …”
Article -
5
Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
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6
Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review
Published 2024“…Furthermore, it is also shown that various machine learning algorithms are used, and the most used are Neural Network and Support Vector Machine. …”
Conference Paper -
7
Investigate And Analysis Of Deep Learning And Machine Learning Algorithm For Face Mask Detection System
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Undergraduates Project Papers -
8
Shot boundary detection based on orthogonal polynomial
Published 2019“…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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9
A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features
Published 2022“…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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10
The development of virtual product life cycle design tool using artificial intelligence technique
Published 2008“…The generated features from code classification algorithm give the information of machining parameter through the mapping algorithm. …”
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Monograph -
11
The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…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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12
Empirical study on intelligent android malware detection based on supervised machine learning
Published 2020“…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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13
Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Undergraduates Project Papers -
14
Web Camera Application For Motion Detection
Published 2003“…The new method to detect motion is "vision motion detection". It is the artificial way of machine vision system compared to human's vision in detecting motion. …”
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Thesis -
15
IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE
Published 2017“…Selected basic behaviour-based algorithms such as wallfollower, obstacle avoidance, escape route and target detection are to be combined and its efficiency is measured. …”
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Final Year Project -
16
Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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Thesis -
17
An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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18
Facial emotion detection using Guided Particle Swarm Optimization (GPSO)
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Working Paper -
19
Estimation of electric vehicle turning radius through machine learning for roundabout cornering
Published 2021“…This paper presents an alternative approach for estimating the turning radius using machine learning technique. While on-board sensors are unable to offer adequate information on vehicle states to the algorithm, vehicle states other than those directly detected by on-board sensors can be inferred using machine learning (ML) approaches based on the collected data. …”
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Conference or Workshop Item -
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