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Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees
Published 2017Get full text
doctoralThesis -
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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022“…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. …”
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Developing an online hate classifier for multiple social media platforms
Published 2020“…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”
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Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis
Published 2023“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Get full text
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis
Published 2023“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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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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Exploring new horizons in neuroscience disease detection through innovative visual signal analysis
Published 2024“…To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. …”
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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
Published 2025Get full text
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Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring
Published 2024“…Our data-driven occupancy detection approach utilized Machine Learning (ML) algorithms to intelligently determine room occupancy, allowing for precise energy management based on real-time usage patterns. …”
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Information reconciliation through agent controlled graph model. (c2018)
Published 2018Get full text
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masterThesis -
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Corrosion Monitoring Technologies for Reinforced Concrete Structures: A Review
Published 2023“…New technology, algorithms, data processing, and AI are new approaches to improving corrosion monitoring processes. …”
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Large-scale annotation dataset for fetal head biometry in ultrasound images
Published 2023“…Its detailed annotations, broad compatibility, and ethical compliance make it a highly reusable and adaptable tool for the development of algorithms aimed at improving maternal and Fetal health.…”
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Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review
Published 2025“…Editorials, expert opinions, conference papers, dataset publications, and studies that did not have a clear clinical application of the AI algorithm were excluded.</p><h3>Results</h3><p dir="ltr">345 articles were identified, following abstract and full-text review by two independent reviewers, 18 manuscripts were included. …”
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Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review
Published 2022“…PCs were the most common platform used to play serious games. The most common algorithm used in the included studies was support vector machine. …”
