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Modern computer vision with PyTorch : = a practical roadmap from deep learning fundamentals to advanced applications and Generative AI /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Modern computer vision with PyTorch :/ V. Kishore Ayyadevara, Yeshwanth Reddy.
其他題名:	a practical roadmap from deep learning fundamentals to advanced applications and Generative AI /
其他題名:	Practical roadmap from deep learning fundamentals to advanced applications and Generative AI
作者:	Ayyadevara, V. Kishore.
其他作者:	Reddy, Yeshwanth.
出版者:	Birmingham, UK :Packt Publishing Ltd., : c2024.,
面頁冊數:	xxiv, 716 p. :ill. ; : 24 cm.;
附註:	Includes index.
標題:	Machine learning. -
ISBN:	9781803231334 (pbk.) :

Modern computer vision with PyTorch : = a practical roadmap from deep learning fundamentals to advanced applications and Generative AI /
Ayyadevara, V. Kishore.

Modern computer vision with PyTorch :a practical roadmap from deep learning fundamentals to advanced applications and Generative AI /Practical roadmap from deep learning fundamentals to advanced applications and Generative AIV. Kishore Ayyadevara, Yeshwanth Reddy. - 2nd ed. - Birmingham, UK :Packt Publishing Ltd.,c2024. - xxiv, 716 p. :ill. ;24 cm. - Expert insight. - Expert insight..

Includes index.

Whether you are a beginner or are looking to progress in your computer vision career, this book guides you through the fundamentals of neural networks (NNs) and PyTorch and how to implement state-of-the-art architectures for real-world tasks. The second edition of Modern Computer Vision with PyTorch is fully updated to explain and provide practical examples of the latest multimodal models, CLIP, and Stable Diffusion. You'll discover best practices for working with images, tweaking hyperparameters, and moving models into production. As you progress, you'll implement various use cases for facial keypoint recognition, multi-object detection, segmentation, and human pose detection. This book provides a solid foundation in image generation as you explore different GAN architectures. You'll leverage transformer-based architectures like ViT, TrOCR, BLIP2, and LayoutLM to perform various real-world tasks and build a diffusion model from scratch. Additionally, you'll utilize foundation models' capabilities to perform zero-shot object detection and image segmentation. Finally, you'll learn best practices for deploying a model to production. By the end of this deep learning book, you'll confidently leverage modern NN architectures to solve real-world computer vision problems.

ISBN: 9781803231334 (pbk.) :NT1987Subjects--Topical Terms:

561253
Machine learning.

LC Class. No.: TA1634

Dewey Class. No.: 006.3/7 / A989

Modern computer vision with PyTorch : = a practical roadmap from deep learning fundamentals to advanced applications and Generative AI /
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