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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…With SSA optimization, the Sauvola method combined with SVM reaches an accuracy of 99.58%, surpassing other methods that use image processing and ANN classification. …”
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2
A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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3
Kinect-based human gait recognition using locally linear embedded and support vector machine
Published 2018“…Next, the extracted gait features were then optimized using LLE known as DG-LLE and further classified by multi-class SVM with Error Correcting Output Code (ECOC) algorithm. …”
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4
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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5
Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…The third proposed segmentation algorithm involves two pipelines for feature extraction: split & merge methods and Contextual Encoding Network (EncNet) with an attention mechanism. …”
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6
P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…In this research the BCI competition data-set has been processed through 5 optimized detection methods. Wavelet transform (WT), student’s two-sample t-statistic (T-Test) and support vector machines (SVM) used in designing the algorithms. …”
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7
Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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8
Discrete wavelet packet transform for electroencephalogram based valence-arousal emotion recognition
Published 2015“…The aim of this study is to discover the feature extraction method and the combination of electrode channels that optimally implements EEG-based valencearousal emotion recognition. …”
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9
Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…Comparisons were made between the proposed method to the k-nearest neighbor (KNN) and support vector machine (SVM), methods for image segmentation. …”
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Specific heat capacity extraction of soybean oil/mxene nanofluids using optimized long short-term memory
Published 2024“…This study employs a long short-term memory (LSTM) as an efficient machine learning method to extract the surrogate model for calculating the cpNF based on the temperature and nanoflakes concentration. …”
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Drowsiness Detection Using Ocular Indices from EEG Signal
Published 2022“…In this study, we used the BLINKER algorithm to extract 25 blink-related features from a public dataset comprising raw EEG signals collected from 12 participants. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah
Published 2012“…Then, Image segmentation applied by using canny edge detection algorithm with specific morphological operation to isolate the image objects components. …”
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Solving SVM model selection problem using ACOR and IACOR
Published 2013“…Ant Colony Optimization (ACO) has been used to solve Support Vector Machine (SVM) model selection problem.ACO originally deals with discrete optimization problem. …”
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