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data detection » data injection (Expand Search)
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121
Artificial Intelligence for Skin Cancer Detection: Scoping Review
Published 2021“…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…”
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122
Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Cyberbullying involves the use of communication technology and data, including messages, photographs, and videos, to undertake aggressive negative actions to harm others. …”
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123
Plant disease detection using drones in precision agriculture
Published 2023“…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”
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124
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125
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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doctoralThesis -
126
Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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127
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…Various clustering methods are available, including K-means, hierarchical clustering, and density-based clustering. …”
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masterThesis -
128
Using genetic algorithms to optimize software quality estimation models
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masterThesis -
129
Simulated annealing and genetic algorithms for exam scheduling. (c1997)
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masterThesis -
130
Bee colony algorithm for assigning proctors to exams. (c2013)
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masterThesis -
131
A Scatter search algorithm for exam scheduling. (c2006)
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masterThesis -
132
Second-order conic programming for data envelopment analysis models
Published 2022“…Data envelopment analysis (DEA) is a widely used benchmarking technique. …”
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133
Data mining approach to predict student's selection of program majors
Published 2019“…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
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134
A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008)
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masterThesis -
135
Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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136
Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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137
Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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138
Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The data from four commercial fields in Atlantic Canada (including Tracadie, Frank Webb, Small Scott, and Cooper fields) were utilized to achieve the goal. …”
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139
A method for optimizing test bus assignment and sizing for system-on-a-chip
Published 2017“…We present experimental results that demonstrate the effectiveness of our method while outperforming reported techniques.…”
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conferenceObject -
140
Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning
Published 2023“…Individuals may have catastrophic side effects from that as well, including despair, anxiety, and even suicide. Due to the difficulty of manually detecting and categorizing vast volumes of electronic text data, conventional methods for recognizing and combating cyberbullying have not proven successful. …”
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