A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) (Inglés) Tapa blanda – 13 febrero 2018
A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) (Inglés) Tapa blanda – 13 febrero 2018 de Salman Khan online free pdf Salman Khan descarga de libros mobi - Descarga este hermoso libro de A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) (Inglés) Tapa blanda – 13 febrero 2018 y léelo más tarde. ¿Tienes curiosidad por saber quién escribió este gran libro? Sí, Salman Khan es el autor de A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) (Inglés) Tapa blanda – 13 febrero 2018. Este libro consta de varias páginas 208 páginas. Morgan & Claypool Publishers (13 febrero 2018) es la empresa que publica A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) (Inglés) Tapa blanda – 13 febrero 2018 al público. 13 febrero 2018 es la primera fecha de lanzamiento. Lea el A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) (Inglés) Tapa blanda – 13 febrero 2018 ahora, es el tema más interesante. Sin embargo, si no tienes mucho tiempo para leer, puedes descargar A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) (Inglés) Tapa blanda – 13 febrero 2018 en tu dispositivo y verlo más tarde.
e serez pas déçu par le contenu. Vous pouvez télécharger A Guide to Convolutional Neural Networks for Computer Vision (Synthesis Lectures on Computer Vision) (Inglés) Tapa blanda – 13 febrero 2018 à votre ordinateur avec des étapes modestes./p>Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation. This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.
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