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Creating and detecting fake reviews of online products
Published 2022“…In this research, we address the creation and detection of fake reviews. First, we experiment with two language models, ULMFiT and GPT-2, to generate fake product reviews based on an Amazon e-commerce dataset. …”
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144
Deepfakes Signatures Detection in the Handcrafted Features Space
Published 2023“…We, therefore, Propose in this paper, a handcrafted feature based Writer-Independent (WI) signature verification system to detect synthetic writers and signatures through handcrafted features. …”
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145
Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks
Published 2010Get full text
doctoralThesis -
146
Machine Learning Model for a Sustainable Drilling Process
Published 2023Get full text
doctoralThesis -
147
Recent Advances of Chimp Optimization Algorithm: Variants and Applications
Published 2023“…Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. …”
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148
Data redundancy management for leaf-edges in connected environments
Published 2022“…Major advances in the fields of Internet and Communication Technology (ICT), data modeling/processing, and sensing technology have rendered traditional environments (e.g., cities, buildings) more connected. …”
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149
A hybrid graph representation for recursive backtracking algorithms
Published 2017“…The performance of these algorithms often suffers from the increasing number of graph modifications, such as deletions, that reduce the problem instance and have to be “taken back” frequently during the search process. …”
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conferenceObject -
150
The effects of data balancing approaches: A case study
Published 2023“…Our results showed that the replacement method was effective, and LogisticRegression combined with the oversampling algorithms SMOTE or ADASYN, GaussianProcessClassifier with the oversampling algorithm SMOTE, and LinearDiscriminantAnalysis were the best performing models after log transformation of the dataset was followed by Recursive Feature Elimination.…”
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151
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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152
Computer-aided detection of Melanoma using geometric features
Published 2017“…The k-Nearest Neighbors (k-NN) machine learning algorithm is used to classify 15 lesions based on their ABD features. …”
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conferenceObject -
153
Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…If conducted automatically, rather than relying on human moderators, the process will be faster, enabling the early detection of cyberbullying before severe harm is caused. …”
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154
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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Big Data Energy Management, Analytics and Visualization for Residential Areas
Published 2020“…A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. …”
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156
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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doctoralThesis -
157
An efficient approach for textual data classification using deep learning
Published 2022“…Textual data contains much useless information that must be pre-processed. …”
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158
Bee colony algorithm for assigning proctors to exams. (c2013)
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masterThesis -
159
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…The proposed method, named Eye-means, emulates the natural ocular process of estimating initial centroids. To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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masterThesis -
160
Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…Whilst different models are proposed for STLF, they are based on small historical datasets and are not scalable to process large amounts of big data as energy consumption data grow exponentially in large electric distribution networks. …”