Multi-label deep learning for comprehensive optic nerve head segmentation through data of fundus images

Multi-label deep learning for comprehensive optic nerve head segmentation through data of fundus images

By Najdavan Abduljawad Kako | Heliyonhttps://www.sciencedirect.com/science/article/pii/S2405844024130277Early diagnosis and continuous monitoring of patients with eye diseases are critical in computer-aided detection (CAD) techniques. Semantic segmentation, a…

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Predicting strength and strain of circular concrete cross-sections confined with FRP under axial compression by utilizing ANN

Predicting strength and strain of circular concrete cross-sections confined with FRP under axial compression by utilizing ANN

By Yaman Sami Shareef | Computers and Concretehttps://doi.org/10.12989/cac.2024.34.1.093One well-known reason for using Fiber Reinforced Polymer (FRP) composites is to improve concrete strength and strain capacity via external confinement. Hence, various stud…

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Comparative Analysis of Classical Machine Learning and Deep Learning Methods for Fruit Image Recognition and Classification

Comparative Analysis of Classical Machine Learning and Deep Learning Methods for Fruit Image Recognition and Classification

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Comparative analysis of medicinal plants from Kurdistan region-Iraq for chemical constituents and bioactivities

Comparative analysis of medicinal plants from Kurdistan region-Iraq for chemical constituents and bioactivities

By Anwer Normohamad Mamdoh | Plant Science Todayhttps://doi.org/10.14719/pst.3582The medicinal plants in Kurdistan-Iraq are used widely for the treatment of many diseases. Therefore, it is very interesting to look after the components of these plants as they …

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Improving Autonomous Vehicle Perception through Evaluating LiDAR Capabilities and Handheld Retroreflectivity Assessments

Improving Autonomous Vehicle Perception through Evaluating LiDAR Capabilities and Handheld Retroreflectivity Assessments

By Ziyad Nayef Shamsulddin | Sensorshttps://www.mdpi.com/1424-8220/24/11/3304Road safety is a serious concern worldwide, and traffic signs play a critical role in confirming road safety, particularly in the context of AVs. Therefore, there is a need for ongoi…

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Diabetic retinopathy detection using Bilayered Neural Network classification model with resubstitution validation

Diabetic retinopathy detection using Bilayered Neural Network classification model with resubstitution validation

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EEG-Based Autism Detection Using Multi-Input 1D Convolutional Neural Networks

EEG-Based Autism Detection Using Multi-Input 1D Convolutional Neural Networks

By Naaman Omar Yaseen | Traitement du Signalhttps://doi.org/10.18280/ts.410128Autism Spectrum Disorder (ASD) is a complex condition affecting children and characterized by challenges in social interaction, communication, and behavior. Typically, evident befor…

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Cybernet Model: A New Deep Learning Model for Cyber DDoS Attacks Detection and Recognition

Cybernet Model: A New Deep Learning Model for Cyber DDoS Attacks Detection and Recognition

By Azar Abid Salih | Computers, Materials & ContinuaDOI: 10.32604/cmc.2023.046101Cyberspace is extremely dynamic, with new attacks arising daily. Protecting cybersecurity controls is vital for network security. Deep Learning (DL) models find widespread us…

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Molecular Characterization of Hemophilia A Patients in Duhok, Iraq

Molecular Characterization of Hemophilia A Patients in Duhok, Iraq

By Najeeb Saeed Rasheed I Pharmacophorehttps://doi.org/10.51847/YerIDDpIcmThe gene for coagulation factor VIII in hemophilia has more than 250 distinct mutations, and documentation of these mutations can predict the clinical phenotype, the likelihood of devel…

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Flag-Based Vehicular Clustering Scheme for Vehicular Ad-Hoc Networks

Flag-Based Vehicular Clustering Scheme for Vehicular Ad-Hoc Networks

By Fady Esmat Fathel Samann | CMChttps://doi.org/10.32604/cmc.2023.043580 Clustering schemes in vehicular networks organize vehicles into logical groups. They are vital for improving network performance, accessing the medium, and enabling efficient data disse…

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