yadav kumar ashutosh (33 résultats)

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Etat : New. SUPER FAST SHIPPING.

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Hardback. Etat : New. New copy - Usually dispatched within 4 working days. 185.

Etat : New.

Hardback. Etat : New. 1st. The goal of this book is to facilitate and stimulate cross-disciplinary research in the emerging paradigm of Medical Imaging. Especially this book is to focus on analysing and articulating proven and potential security measures to tightly secure Medical Image applications and services, which are being hosted and delivered through cloud infrastructures and platforms. This book will illustrate the prominent advancements in image processing and how intelligent image-processing techniques can be developed and deployed in the industrial market and for academicians. The readers will get to know all the right and relevant details to be empowered to successfully contribute to their personal and professional growth. The main focus of this book is to bring all the related technologies, novel findings, and managerial applications of Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to Researchers in Medical Engineers, Machine Learning and Data Analysis.

Etat : As New. Unread book in perfect condition.

Etat : New. 1st edition NO-PA16APR2015-KAP.

Etat : New. In.

Etat : As New. Unread book in perfect condition.

Etat : New.

Hardback. Etat : New. 1st. The goal of this book is to facilitate and stimulate cross-disciplinary research in the emerging paradigm of Medical Imaging. Especially this book is to focus on analysing and articulating proven and potential security measures to tightly secure Medical Image applications and services, which are being hosted and delivered through cloud infrastructures and platforms. This book will illustrate the prominent advancements in image processing and how intelligent image-processing techniques can be developed and deployed in the industrial market and for academicians. The readers will get to know all the right and relevant details to be empowered to successfully contribute to their personal and professional growth. The main focus of this book is to bring all the related technologies, novel findings, and managerial applications of Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to Researchers in Medical Engineers, Machine Learning and Data Analysis.

Etat : New. Dr. Satya Prakash Yadav (SMIEEE) is currently the Associate Professor of the School of Computer Science Engineering and Technology (SCSET), Bennett University, Greater Noida (India) and has completed his Postdoctoral Research Fel.

Hardcover. Etat : new. Hardcover. The goal of this book is to facilitate and stimulate cross-disciplinary research in the emerging paradigm of Medical Imaging. Especially this book is to focus on analysing and articulating proven and potential security measures to tightly secure Medical Image applications and services, which are being hosted and delivered through cloud infrastructures and platforms. This book will illustrate the prominent advancements in image processing and how intelligent image-processing techniques can be developed and deployed in the industrial market and for academicians. The readers will get to know all the right and relevant details to be empowered to successfully contribute to their personal and professional growth. The main focus of this book is to bring all the related technologies, novel findings, and managerial applications of Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to Researchers in Medical Engineers, Machine Learning and Data Analysis. This book develops a high-resolution multi-spectral image that both contain high-resolution panchromatic spatial information and multi-spectral image color information for denoising, reconstruction, classification, color image hallucination, feature Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Hardcover. Etat : Brand New. 397 pages. 9.44x6.69x9.61 inches. In Stock.

Hardcover. Etat : Brand New. 348 pages. 9.19x6.13x1.10 inches. In Stock.

Etat : New. In.

Buch. Etat : Neu. Neuware - The goal of this book is to facilitate and stimulate cross-disciplinary research in the emerging paradigm of Medical Imaging. Especially this book is to focus on analysing and articulating proven and potential security measures to tightly secure Medical Image applications and services, which are being hosted and delivered through cloud infrastructures and platforms. This book will illustrate the prominent advancements in image processing and how intelligent image-processing techniques can be developed and deployed in the industrial market and for academicians. The readers will get to know all the right and relevant details to be empowered to successfully contribute to their personal and professional growth. The main focus of this book is to bring all the related technologies, novel findings, and managerial applications of Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to Researchers in Medical Engineers, Machine Learning and Data Analysis.

Paperback. Etat : new. Paperback. Natural Language Processing (NLP) is transforming mental health care by enabling early detection, diagnosis, and intervention for conditions such as depression, PTSD, and suicidal ideation. Advanced AI models like BioBERT and Med-BERT help analyze speech patterns, cognitive behaviors, and psychological markers to support medical practitioners in providing more effective and timely care. By leveraging deep learning and AI-driven assessments, NLP can enhance behavioral monitoring, improve treatment personalization, and optimize mental health interventions. As global mental health challenges continue to rise, integrating NLP into healthcare systems presents a crucial step toward more accessible, data-driven, and proactive mental health support. Demystifying the Role of Natural Language Processing (NLP) in Mental Health explores the latest advancements in NLP for mental health care, highlighting its role in diagnosing and treating conditions like depression, PTSD, and suicidal ideation. It examines AI-driven models, speech analysis, and behavioral monitoring techniques that enhance early intervention and personalized treatment strategies. Covering topics such as suicidal identification, emotional recognition, and patient response, this book is an excellent resource for mental health practitioners, medical practitioners, social workers, computer scientists, professionals, researchers, scholars, academicians, and more. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Etat : new. Paperback. Natural Language Processing (NLP) is transforming mental health care by enabling early detection, diagnosis, and intervention for conditions such as depression, PTSD, and suicidal ideation. Advanced AI models like BioBERT and Med-BERT help analyze speech patterns, cognitive behaviors, and psychological markers to support medical practitioners in providing more effective and timely care. By leveraging deep learning and AI-driven assessments, NLP can enhance behavioral monitoring, improve treatment personalization, and optimize mental health interventions. As global mental health challenges continue to rise, integrating NLP into healthcare systems presents a crucial step toward more accessible, data-driven, and proactive mental health support. Demystifying the Role of Natural Language Processing (NLP) in Mental Health explores the latest advancements in NLP for mental health care, highlighting its role in diagnosing and treating conditions like depression, PTSD, and suicidal ideation. It examines AI-driven models, speech analysis, and behavioral monitoring techniques that enhance early intervention and personalized treatment strategies. Covering topics such as suicidal identification, emotional recognition, and patient response, this book is an excellent resource for mental health practitioners, medical practitioners, social workers, computer scientists, professionals, researchers, scholars, academicians, and more. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Etat : New. In.

Hardcover. Etat : new. Hardcover. Natural Language Processing (NLP) is transforming mental health care by enabling early detection, diagnosis, and intervention for conditions such as depression, PTSD, and suicidal ideation. Advanced AI models like BioBERT and Med-BERT help analyze speech patterns, cognitive behaviors, and psychological markers to support medical practitioners in providing more effective and timely care. By leveraging deep learning and AI-driven assessments, NLP can enhance behavioral monitoring, improve treatment personalization, and optimize mental health interventions. As global mental health challenges continue to rise, integrating NLP into healthcare systems presents a crucial step toward more accessible, data-driven, and proactive mental health support. Demystifying the Role of Natural Language Processing (NLP) in Mental Health explores the latest advancements in NLP for mental health care, highlighting its role in diagnosing and treating conditions like depression, PTSD, and suicidal ideation. It examines AI-driven models, speech analysis, and behavioral monitoring techniques that enhance early intervention and personalized treatment strategies. Covering topics such as suicidal identification, emotional recognition, and patient response, this book is an excellent resource for mental health practitioners, medical practitioners, social workers, computer scientists, professionals, researchers, scholars, academicians, and more. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Etat : new. Paperback. Natural Language Processing (NLP) is transforming mental health care by enabling early detection, diagnosis, and intervention for conditions such as depression, PTSD, and suicidal ideation. Advanced AI models like BioBERT and Med-BERT help analyze speech patterns, cognitive behaviors, and psychological markers to support medical practitioners in providing more effective and timely care. By leveraging deep learning and AI-driven assessments, NLP can enhance behavioral monitoring, improve treatment personalization, and optimize mental health interventions. As global mental health challenges continue to rise, integrating NLP into healthcare systems presents a crucial step toward more accessible, data-driven, and proactive mental health support. Demystifying the Role of Natural Language Processing (NLP) in Mental Health explores the latest advancements in NLP for mental health care, highlighting its role in diagnosing and treating conditions like depression, PTSD, and suicidal ideation. It examines AI-driven models, speech analysis, and behavioral monitoring techniques that enhance early intervention and personalized treatment strategies. Covering topics such as suicidal identification, emotional recognition, and patient response, this book is an excellent resource for mental health practitioners, medical practitioners, social workers, computer scientists, professionals, researchers, scholars, academicians, and more. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Etat : new. Hardcover. Natural Language Processing (NLP) is transforming mental health care by enabling early detection, diagnosis, and intervention for conditions such as depression, PTSD, and suicidal ideation. Advanced AI models like BioBERT and Med-BERT help analyze speech patterns, cognitive behaviors, and psychological markers to support medical practitioners in providing more effective and timely care. By leveraging deep learning and AI-driven assessments, NLP can enhance behavioral monitoring, improve treatment personalization, and optimize mental health interventions. As global mental health challenges continue to rise, integrating NLP into healthcare systems presents a crucial step toward more accessible, data-driven, and proactive mental health support. Demystifying the Role of Natural Language Processing (NLP) in Mental Health explores the latest advancements in NLP for mental health care, highlighting its role in diagnosing and treating conditions like depression, PTSD, and suicidal ideation. It examines AI-driven models, speech analysis, and behavioral monitoring techniques that enhance early intervention and personalized treatment strategies. Covering topics such as suicidal identification, emotional recognition, and patient response, this book is an excellent resource for mental health practitioners, medical practitioners, social workers, computer scientists, professionals, researchers, scholars, academicians, and more. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Etat : new. Hardcover. Natural Language Processing (NLP) is transforming mental health care by enabling early detection, diagnosis, and intervention for conditions such as depression, PTSD, and suicidal ideation. Advanced AI models like BioBERT and Med-BERT help analyze speech patterns, cognitive behaviors, and psychological markers to support medical practitioners in providing more effective and timely care. By leveraging deep learning and AI-driven assessments, NLP can enhance behavioral monitoring, improve treatment personalization, and optimize mental health interventions. As global mental health challenges continue to rise, integrating NLP into healthcare systems presents a crucial step toward more accessible, data-driven, and proactive mental health support. Demystifying the Role of Natural Language Processing (NLP) in Mental Health explores the latest advancements in NLP for mental health care, highlighting its role in diagnosing and treating conditions like depression, PTSD, and suicidal ideation. It examines AI-driven models, speech analysis, and behavioral monitoring techniques that enhance early intervention and personalized treatment strategies. Covering topics such as suicidal identification, emotional recognition, and patient response, this book is an excellent resource for mental health practitioners, medical practitioners, social workers, computer scientists, professionals, researchers, scholars, academicians, and more. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

HRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.