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3D Deep Learning with Python - Design and develop your computer vision model with 3D data using PyTorch3D and more (Paperback) Loot Price: R1,087
Discovery Miles 10 870
3D Deep Learning with Python - Design and develop your computer vision model with 3D data using PyTorch3D and more (Paperback):...

3D Deep Learning with Python - Design and develop your computer vision model with 3D data using PyTorch3D and more (Paperback)

Xudong Ma, Vishakh Hegde, Lilit Yolyan

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Loot Price R1,087 Discovery Miles 10 870 | Repayment Terms: R102 pm x 12*

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Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with ease Key Features Understand 3D data processing with rendering, PyTorch optimization, and heterogeneous batching Implement differentiable rendering concepts with practical examples Discover how you can ease your work with the latest 3D deep learning techniques using PyTorch3D Book DescriptionWith this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time. Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library. By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. What you will learn Develop 3D computer vision models for interacting with the environment Get to grips with 3D data handling with point clouds, meshes, ply, and obj file format Work with 3D geometry, camera models, and coordination and convert between them Understand concepts of rendering, shading, and more with ease Implement differential rendering for many 3D deep learning models Advanced state-of-the-art 3D deep learning models like Nerf, synsin, mesh RCNN Who this book is forThis book is for beginner to intermediate-level machine learning practitioners, data scientists, ML engineers, and DL engineers who are looking to become well-versed with computer vision techniques using 3D data.

General

Imprint: Packt Publishing Limited
Country of origin: United Kingdom
Release date: October 2022
Authors: Xudong Ma • Vishakh Hegde • Lilit Yolyan
Dimensions: 93 x 75mm (L x W)
Format: Paperback
Pages: 236
ISBN-13: 978-1-80324-782-3
Categories: Books > Computing & IT > General theory of computing > Mathematical theory of computation
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks
LSN: 1-80324-782-7
Barcode: 9781803247823

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