Jayagopal prabhu (32 Ergebnisse)

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Zustand: New. Dr Saurav Mallik is a Research Scientist in the Department of Pharmacology and Toxicology, The University of Arizona, USA. Prior to this, he was a Postdoctoral Fellow in the Department of Environmental Health, Harvard T H Chan School of Public Hea.

Taschenbuch. Zustand: Neu. Neuware - Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medical diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research. Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering.…

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Zustand: New. 2026. 1st Edition. hardcover. . . . . .

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Buch. Zustand: Neu. Neuware - Advancements in sensor technology have enabled autonomous systems to operate efficiently and safely in the Internet of Vehicles environment. Multisensor image fusion is a crucial component in enhancing the capabilities of these autonomous systems by combining information from multiple sensors such as cameras, LiDAR, radar, and ultrasonic sensors. This book delves into the role of multisensor image fusion in the Internet of Vehicles for autonomous systems. It will cover the fundamental concepts of multisensor image fusion, different fusion methods, and their applications in autonomous systems for the IoV. It will also address the challenges associated with multisensor fusion, such as sensor calibration, synchronization, and noise reduction and discuss the benefits of multisensor fusion in improving object detection, tracking, and decision-making processes in autonomous vehicles operating in the IoV. This book is a comprehensive overview of multisensor image fusion in the context of IoV for autonomous systems, highlighting its importance in achieving reliable and robust autonomous navigation in dynamic and complex environments.…

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Hardback. Zustand: New. Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medical diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research. Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering.…