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Destinazione, tempi e costiDa: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Ben Othman Soufiene was Assistant Professor of computer science at the University of Gabes, Tunisia, from 2016 to 2021. He received his PhD in computer science from Manouba University in 2016 for his dissertation on secure data aggregati. Codice articolo 899835621
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples.Features:Offers important key aspects in the development and implementation of machine learning anddeep learningapproaches toward developing prediction tools and models and improving medical diagnosisTeaches howmachine learninganddeep learningalgorithms are applied to a broad range of application areas, including chest X-ray, breast computer-aided detection, lung and chest, microscopy, and pathologyCovers common research problems in medical image analysis and their challengesFocuses on aspects of deep learning and machine learning for combating COVID-19Includes pertinent case studies This book is aimed at researchers and graduate students in computer engineering, artificial intelligence and machine learning, and biomedical imaging. 258 pp. Englisch. Codice articolo 9781032416168
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 46259588
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days. 660. Codice articolo B9781032416168
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Codice articolo 399832431
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Da: AHA-BUCH GmbH, Einbeck, Germania
Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples.Features:Offers important key aspects in the development and implementation of machine learning anddeep learningapproaches toward developing prediction tools and models and improving medical diagnosisTeaches howmachine learninganddeep learningalgorithms are applied to a broad range of application areas, including chest X-ray, breast computer-aided detection, lung and chest, microscopy, and pathologyCovers common research problems in medical image analysis and their challengesFocuses on aspects of deep learning and machine learning for combating COVID-19Includes pertinent case studies This book is aimed at researchers and graduate students in computer engineering, artificial intelligence and machine learning, and biomedical imaging. Codice articolo 9781032416168
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. Codice articolo 26396577456
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 46259588-n
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