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:
This book is aimed at researchers and graduate students in computer engineering, artificial intelligence and machine learning, and biomedical imaging.
"Sinopsis" puede pertenecer a otra edición de este libro.
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 aggregation in wireless sensor networks. He also earned an MS from Monastir University in 2012. His research interests focus on the Internet of Medical Things, wireless body sensor networks, wireless networks, artificial intelligence, machine learning, and big data.
Chinmay Chakraborty is Assistant Professor in the Department of Electronics and Communication Engineering, BIT Mesra, India, and a Postdoctoral Fellow of the Federal University of Piauí, Brazil. His primary areas of research include wireless body area networks, Internet of Medical Things (IoMT), point-of-care diagnosis, mHealth/e-health, and medical imaging. Chakraborty is the co-editor of many books on Smart IoMT, healthcare technology, and sensor data analytics.
This book 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 supported by case studies.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 46259588
Cantidad disponible: 1 disponibles
Librería: moluna, Greven, Alemania
Condición: 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. Nº de ref. del artículo: 899835621
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: New. Nº de ref. del artículo: 46259588-n
Cantidad disponible: 1 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 46259588
Cantidad disponible: 1 disponibles
Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Nº de ref. del artículo: 399832431
Cantidad disponible: 3 disponibles
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 46259588-n
Cantidad disponible: 1 disponibles
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Buch. Condición: 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. 272 pp. Englisch. Nº de ref. del artículo: 9781032416168
Cantidad disponible: 2 disponibles
Librería: Books Puddle, Woodside, NY, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 26396577456
Cantidad disponible: 3 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L1-9781032416168
Cantidad disponible: Más de 20 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Nº de ref. del artículo: I-9781032416168
Cantidad disponible: Más de 20 disponibles