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Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks
Published 2025“…<h3>Purpose</h3><p dir="ltr">To evaluate image quality (IQ) of for‐processing (raw) and for‐presentation (clinical) radiography images, under different exposure conditions and digital image post‐processing algorithms, using a phantom that enables multiple detection tasks.…”
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Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees
Published 2017Get full text
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Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems
Published 2022“…This is addressed such that the genetic algorithm (GA) technique is used for selecting the best features and the artificial neural network (ANN) classifier is applied for fault diagnosis. …”
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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning
Published 2023“…A sizable dataset of electronic text data was gathered from multiple social media platforms like Twitter, Instagram, YouTube, and many more sites in order to examine cyberbullying in social media using machine learning and deep learning techniques. …”
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…By using a comprehensive dataset with multiple attack types, a well-trained model can be created to improve the anomaly detection performance. …”
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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“…Although researchers have found that hate is a problem across multiple platforms, there is a lack of models for online hate detection using multi-platform data. …”
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Accurate multiple network alignment through context-sensitive random walk
Published 2015“…In this work, we propose a novel multiple network alignment algorithm based on a context-sensitive random walk model. …”
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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“…Our study demonstrates the effectiveness of the FBFT method, achieving impressive accuracies across multiple brain disorders using CNN-based classification. …”
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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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Bridge Structural Health Monitoring Using Mobile Sensor Networks
Published 2022Get full text
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