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lgli/面向高性能计算的深度学习和边缘计算解决方案.pdf
面向高性能计算的深度学习和边缘计算解决方案 🔍
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英语 [en] · 中文 [zh] · PDF · 11.2MB · 2021 · 📘 非小说类图书 · 🚀/lgli/lgrs · Save
描述
This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology.
Erscheinungsdatum: 28.01.2021
备用文件名
lgrsnf/面向高性能计算的深度学习和边缘计算解决方案.pdf
备选标题
Deep Learning and Edge Computing Solutions for High Performance Computing: High Performance Computing and Emerging Healthcare Technologies (EAI/Springer Innovations in Communication and Computing)
备选标题
Deep Learning and Edge Computing Based Solutions for Smart Healthcare: High Performance Computing and Emerging Healthcare Technologies
备选作者
Michał Jacuński; Barbara Brodzińska-Mirowska; Anna Pacześniak; Maria Wincławska
备选作者
Suresh, A.; Paiva, Sara
备选作者
A. Suresh; Sara Paiva
备用出版商
Springer International Publishing : Imprint: Springer
备用出版商
Springer International Publishing AG
备用出版商
Springer Nature Switzerland AG
备用版本
EAI/Springer Innovations in Communication and Computing, 1st ed. 2021, Cham, Cham, 2021
备用版本
EAI/Springer innovations in communication and computing, Cham, Switzerland, 2021
备用版本
Springer Nature, Cham, 2021
备用版本
Switzerland, Switzerland
备用描述
This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology. Identifies deep learning techniques in mobile edge data analytics and computing environments suitable for applications in healthcare; Introduces big data analytics to the sources available and possible challenges and techniques associated with bioinformatics and the healthcare domain; Features advancements in the computing field to effectively handle and make inferences from voluminous and heterogeneous healthcare data
备用描述
This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field --Page [4] of cover
开源日期
2024-02-25
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