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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…Moreover, the image pixels in different and more similar areas of the image are located next to one another in a group and classified using the specified thresholds. As a result, the embedding capacity in each class can increase by reducing the value of the difference between two consecutive pixels, and the distortion of the marked image can decrease after inserting the personal data using the DE method. …”
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An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019Subjects: Get full text
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Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…The main novelty of this work is the computer-aided diagnosis scheme for detecting abnormalities in breast ultrasound images by integrating a wavelet neural network (WNN) and the grey wolf optimization (GWO) algorithm. …”
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …”
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An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…The huge amounts of data generated by media sensors in health monitoring systems, by medical diagnosis that produce media (audio, video, image, and text) content, and from health service providers are too complex and voluminous to be processed and analyzed by traditional methods. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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Automatic image quality evaluation in digital radiography using for‐processing and for‐presentation images
Published 2024“…<h3>Purpose</h3><p dir="ltr">To investigate the impact of digital image post‐processing algorithms on various image quality (IQ) metrics of radiographic images under different exposure conditions.…”
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Using machine learning to support students’ academic decisions
Published 2019“…This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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Allocation and re-allocation of data in a grid using an adaptive genetic algorithm
Published 2006“…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”
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A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net
Published 2023“…Although, there are dedicated audio processing DNNs, yet, many recent models of AE have utilized U-Net: a DNN based on Convolutional Neural Network (CNN), fundamentally developed for image segmentation. …”