A Beginner Guide To Medical Application Development With Deep Convolutional Neural Networks
Download A Beginner Guide To Medical Application Development With Deep Convolutional Neural Networks PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get A Beginner Guide To Medical Application Development With Deep Convolutional Neural Networks book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
A Beginner Guide to Medical Application Development with Deep Convolutional Neural Networks
"This book serves as source of introductory material and reference for medical application development and related technologies by providing the detail implementation of the cutting-edge deep learning methodologies. It targets the cloud based advanced medical application developments using open-source python based deep learning libraries. It includes code snippets and sophisticated Convolutional Neural Networks (CNNs) to tackle real-world problems in medical image analysis and beyond. The book provides programming guidance for creation of sophisticated and reliable neural networks for image processing and incorporates the comparative study on GAN, Stable diffusion and its application on Medical Image data augmentation. It focusses on solving real world medical imaging problems and discuses advanced concepts of Deep Learning along with latest technology like GPT, Stable Diffusion, ViT. This book is aimed at graduate students and researchers in medical data analytics, medical image analysis, signal processing, and deep learning"--
A Beginner's Guide to Medical Application Development with Deep Convolutional Neural Networks
This book serves as a source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of cutting-edge deep learning methodologies. It targets cloud-based advanced medical application developments using open-source Python-based deep learning libraries. It includes code snippets and sophisticated convolutional neural networks to tackle real-world problems in medical image analysis and beyond. Features: Provides programming guidance for creation of sophisticated and reliable neural networks for image processing. Incorporates the comparative study on GAN, stable diffusion, and its application on medical image data augmentation. Focuses on solving real-world medical imaging problems. Discusses advanced concepts of deep learning along with the latest technology such as GPT, stable diffusion, and ViT. Develops applicable knowledge of deep learning using Python programming, followed by code snippets and OOP concepts. This book is aimed at graduate students and researchers in medical data analytics, medical image analysis, signal processing, and deep learning.
A Beginner's Guide to Introduce Artificial Intelligence in Teaching and Learning
This book reimagines education in today’s Artificial Intelligence (AI) world and the Fourth Industrial Revolution. Artificial intelligence will drastically affect every industry and sector, and education is no exception. This book aims at how AI may impact the teaching and learning process in education. This book is designed to demystify AI for teachers and learners. This book will help improve education and support institutions in the phenomena of the emergence of AI in teaching and learning. This book presents a comprehensive study of how AI improves teaching and learning, from AI-based learning platforms to AI-assisted proctored examinations. This book provides educators, learners, and administrators on how AI makes sense in their everyday practice. Describing the application of AI in ten key aspects, this comprehensive volume prepares educational leaders, designers, researchers, and policymakers to effectively rethink the teaching and learning process and environments that students need to thrive. The readers of this book never fall behind the fast pace and promising innovations of today’s most advanced learning technology.