Ravi vinayakumar (110 résultats)

paperback. Etat : Very Good.

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Etat : As New. Unread book in perfect condition.

Etat : New. In English.

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Etat : As New. Unread book in perfect condition.

Etat : New. 2024th edition NO-PA16APR2015-KAP.

Paperback. Etat : Brand New. 100 pages. 9.25x6.10x9.21 inches. In Stock.

Hardcover. Etat : new. Hardcover. This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Etat : New. A NEW COPY but with very minor shelving/packing damage.; 100% Satisfaction Guaranteed! Ships same or next business day.

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Paperback. Etat : new. Paperback. Self-powered Sensors: A Path to Wearable Electronics Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Etat : new. Hardcover. This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Etat : new. Hardcover. This book offers a comprehensive analysis of intersection of significant domains, including information security, 6G technology, and cybersecurity. This reference work addresses gaps in existing literature by providing insights, research findings, and personal evaluations from esteemed scholars in the field. Holographic-type communications (HTC), tactile Internet, connected autonomous vehicles (CAVs), unmanned aerial vehicles (UAVs), autonomous healthcare solutions, manufacturing systems, and virtual/augmented/extended reality (VR/AR/XR), along with other cutting-edge applications, will continue to advance with the advent of 6G. The advent of the 6G era has been ushered in by the rapid advancement of communication technologies, promising unprecedented applications and connectivity. As we venture into this unexplored domain, the criticality of cybersecurity resilience cannot be overstated. This book examines and assesses the emerging trends in 6G technology, with a particular focus on the intricate challenges encountered in the realm of cybersecurity. By analyzing the intricate interplay between IoT integration, AI/ML security, quantum communication, and the intricacies of the physical layer, this book endeavors to provide a comprehensive understanding of the perpetually evolving threat landscape. It is reasonable to expect that 6G, similar to its predecessors, will promote advancements in the domain of connectivity and telecommunications through the provision of increased data throughput, decreased latency, and expanded capacity. These developments will promote the development of innovative applications and services, thus increasing the importance of robust cybersecurity protocols. As 6G technology continues to proliferate, it becomes increasingly vital to ensure the security and preservation of data.The primary audience of this book is industrialists, academicians, researchers, and UG/PG students. The secondary audience consists of practitioners, cyberpolice, lawmakers, legal firms, etc. as we are also covering regulatory and ethical considerations in 6G cybersecurity. This book offers a comprehensive analysis of intersection of significant domains, including information security, 6G technology, and cybersecurity. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Etat : New. In English.

Etat : New. In English.

Hardcover. Etat : Brand New. 270 pages. 9.26x6.11x9.49 inches. In Stock.

Etat : New. 2024. 1st Edition. paperback. . . . . .

Hardcover. Etat : new. Hardcover. This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

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paperback. Etat : New. New .Ships From Multiple Locations. book.

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction.The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset.…

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of thestate-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.…

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of thestate-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.…

Etat : New. Presents state-of-the-art technologies and advancements in the design and application of self-powered sensorsExamines the advantages and disadvantages of self-powered nanomaterial sensors in terms of energy collecting techniques and sensing.

Taschenbuch. Etat : Neu. Efficient Data Handling for Massive Internet of Medical Things | Healthcare Data Analytics | Chinmay Chakraborty (u. a.) | Taschenbuch | Internet of Things | xiv | Englisch | 2022 | Springer | EAN 9783030666354 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Etat : New.