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Evolving Tsukamoto Neuro Fuzzy Model for Multiclass Covid 19 Classification with Chest X Ray Images
Du e to rapid population growth and the need to use artificial intelligence to make quick decisions, developing a machine learning-based disease detection model and abnormality identification system has greatly improved the level of medical diagnosis Since COVID-19 has become one of the most severe diseases in the world, developing an automatic COVID-19 detection framework helps medical doctors in the diagnostic process of disease and provides correct and fast results.
Generative Adversarial Networks for Brain Images Synthesis: A Review
In medical imaging, image synthesis is the estimation process of one image (sequence, modality) from another image (sequence, modality).
Radiological image synthesis using cycle-consistent generative adversarial network
In medical imaging, image synthesis is the estimation process of one image (sequence, modality) from another image (sequence, modality).
Machine Learning-Based EDoS Attack Detection Technique Using Execution Trace Analysis
In this work, we propose a novel framework to detect different types of EDoS attacks by designing a profile that learns from and classifies the normal and abnormal behaviors.
