Search Results - (( java adaptation optimization algorithm ) OR ( basic detect selection algorithm ))
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1
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
2
A detector generating algorithm for intrusion detection inspired by artificial immune system
Published 2015“…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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3
An ensemble feature selection method to detect web spam
Published 2018“…An ensemble feature selection method has been proposed in this paper to detect web spam. …”
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4
Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
Published 2011“…Three types of March algorithms which are March 17N, March 12N and MarchPS 23N are selected to validate the tool in term of their compatibility for NPSF detection and diagnosis.Suitable data background is identified and a test procedure is developed for each algorithm. …”
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5
Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours
Published 2010“…An approach that detects steady state value for calling genetic algorithm (GA) is proposed to overcome the problems of good classifiers deletion and the local minima trap. …”
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…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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8
Moving detection using cellular neural network (CNN)
Published 2008“…The video then are segmented into images using SC Video Developer. Ten images are selected to be used in this project. The algorithm created is used to detect the ball in the images. …”
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Undergraduates Project Papers -
9
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This improved algorithm, known as the edge-template Contour Delineation (etCD), is based on the fusion of edge detection with corner-template detection and dynamic thresholding to produce enhanced edge map. …”
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10
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 -
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Classification of herbs plant diseases via hierarchical dynamic artificial neural network
Published 2010“…This paper is to propose an unsupervised diseases pattern recognition and classification algorithm that is based on a modified Hierarchical Dynamic Artificial Neural Network which provides an adjustable sensitivity-specificity herbs diseases detection and classification from the analysis of noise-free colored herbs images. …”
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12
Early detection of spots high water saturation for landslide prediction using thermal imaging analysis
“…Hence, to solve this issue, this study investigates a new method to detect water saturation spots which is integrated with a thermal image camera to provide early detection of landslide. …”
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Research Report -
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Medical diagnosis using data mining techniques / Shaiful Nizam Zamri
Published 2003“…Secondly, this report will review the literature part which started with basic knowledge of data mining and knowing what the basic information about data mining. …”
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14
Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework
Published 2011“…This paper is to propose an unsupervised diseases pattern recognition and classification algorithm that is based on a modified Hierarchical Dynamic Artificial Neural Network which provides an adjustable sensitivity-specificity herbs diseases detection and classification from the analysis of noise-free colored herbs images. …”
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15
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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16
An enhance embedding method using edge and textures detection for image steganography
Published 2024“…By embedding in noisy zones using edge and texture detection which complicates feature extraction, making hidden information more secure and statistically less detectable than basic LSB matching techniques. …”
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17
Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…Thus, this research is aimed to develop two models. First, the BrC detection model is developed to diagnose BrT basic types like benign and malignant. …”
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18
Early detection of high water saturation spots for landslide prediction using thermal image analysis
Published 2018“…Hence, to solve this issue, this study investigates a new method to detect water saturation spots which is integrated with a thermal image camera to provide early detection of landslide. …”
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19
Vision Based Calibration and Localization Technique for Video Sensor Networks
Published 2009“…The literature is replete with many localization and calibration algorithms that basically rely on some a-priori chosen nodes, called seeds, with known coordinates to help determine the network topology. …”
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20
Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks
Published 2024“…The results of the tests indicated increased performance in terms of fewer false positives, less CPU utilisation, less control channel bandwidth used, higher packet delivery ratio, and fewer flow requests made to the controller with 99.56% detection accuracy as compared to selected benchmarks. …”
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