Book Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 PDF Download - Uma N. Dulhare, Essam Halim Houssein
Download ebook ➡ http://ebooksharez.info/pl/book/753318/1374
Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2
Uma N. Dulhare, Essam Halim Houssein
Page: 198
Format: pdf, ePub, mobi, fb2
ISBN: 9789819636471
Publisher: Springer Nature Singapore
Download or Read Online Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 Free Book (PDF ePub Mobi) by Uma N. Dulhare, Essam Halim Houssein
Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 Uma N. Dulhare, Essam Halim Houssein PDF, Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 Uma N. Dulhare, Essam Halim Houssein Epub, Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 Uma N. Dulhare, Essam Halim Houssein Read Online, Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 Uma N. Dulhare, Essam Halim Houssein Audiobook, Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 Uma N. Dulhare, Essam Halim Houssein VK, Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 Uma N. Dulhare, Essam Halim Houssein Kindle, Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 Uma N. Dulhare, Essam Halim Houssein Epub VK, Deep Learning and Computer Vision: Models and Biomedical Applications: Volume 2 Uma N. Dulhare, Essam Halim Houssein Free Download
Overview
This book takes a balanced approach between theoretical understanding and real time applications. All topics show how to explore, build, evaluate and optimize deep learning models with computer vision. Deep learning is integrated with computer vision to enhance the performance of image classification with localization, object detection, object recognition, object segmentation, image style transfer, image colorization, image reconstruction, image super-resolution, image synthesis, motion detection, pose estimation, semantic segmentation in biomedical field. Huge number of efficient approaches/applications and models support medical decisions in the fields of cardiology, dermatology, and radiology. The content of book elaborates deep learning models such as convolution neural networks, deep learning, generative adversarial network, long short-term memory networks (LSTM), autoencoder (AE), restricted Boltzmann machine (RBM), self-organizing map (SOM), deep belief network (DBN), etc.