Isbn: 9781032598291 - a beginner's guide to medical application development with deep convolutional neural networks (5 Ergebnisse)
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Beginner's Guide To Medical Application Development With Deep Convolutional Neural Networks
Biswas, Snehan (Iema R&D Pvt. Ltd., India) Mukherjee, Amartya (Institute Of Eng & Manag, Kolkata) Dey, Nilanjan (Jis Univ, India)
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Paperback. Zustand: Brand New. 184 pages. 6.14x0.45x9.21 inches. In Stock.
Beginner s Guide to Medical Application Development with Deep Convolutional Neural Networks
Snehan Biswas (IEMA R&D Pvt. Ltd., India)|Amartya Mukherjee (Institute of Eng & Manag, Kolkata)|Nilanjan Dey (JIS Univ, India)
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Zustand: New. Snehan Biswas, is a Senior System Analyst in the department of Machine Learning and IoT, IEMA Research & Development Private Limited, India. He is a graduate in Electronics & Communication Engineering from University of Engineering and Man.
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Taschenbuch. Zustand: Neu. Neuware - 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.…
