Search Results - (( java application matching algorithm ) OR ( basic classification issues algorithm ))
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Power line faults classification by neural network train by Ant Colony Optimization
Published 2017“…Metaheuristic algorithms are algorithms which, in order to escape from local optima, drive some basic heuristic: either a constructive heuristic starting from a null solution and adding elements to build a good complete one, or a local search heuristic starting from a complete solution and iteratively modifying some of its elements in order to achieve a better one. …”
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Student Project -
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Email spam classification based on deep learning methods: A review
Published 2025“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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Thesis -
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…However, the training datasets usually compose feature sets of irrelevant or redundant information, which impacts the performance of classification, and traditional learning algorithms such as backpropagation suffer from known issues, including slow convergence and the trap of local minimum. …”
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BONE AGE ANALYSIS FROM BONE X-RAY
Published 2018“…Manual bone age assessment basically take time f task in for radiologist and there are always issue related to intra observer and inter observer differences. …”
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Final Year Project -
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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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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Satellite Image Segmentation Using Thresholding Technique
Published 2017“…Image segmentation is one of the basic techniques of image processing and computer vision. …”
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Thesis -
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Message based random variable length key encryption algorithm.
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Securing cloud data system (SCDS) for key exposure using AES algorithm
Published 2021“…The AES algorithm has its own structure to encrypt and decrypt sensitive data that make the attackers difficult to get the real data when encrypting by AES algorithm. …”
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Thesis -
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An ensemble feature selection method to detect web spam
Published 2018“…In addition, it improves classification metrics in comparison to basic feature selection methods.…”
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A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features
Published 2022“…Furthermore, using the basic features, TLSMalDetect achieved the highest accuracy of 93.69% by Naïve Bayes (NB) among the ML algorithms applied. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
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Thesis -
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Early detection of spots high water saturation for landslide prediction using thermal imaging analysis
“…The performance of these segmentation algorithms are measured using misclassification error. …”
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Research Report -
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A review of Convolutional Neural Networks in Remote Sensing Image
Published 2019“…Recently, convolutional neural network based deep learning algorithm has achieved a series of breakthrough research results in the fields of objective detection, image semantic segmentation and image classification, etc. …”
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