Generative AI for Remote Sensing by Vishakha Sood (.PDF)
File Size: 47.8 MB
Generative AI for Remote Sensing of the Environment: Algorithms and Applications by Vishakha Sood, Arun Lal Srivastav, Ravneet Kaur, Neha Bhati
Requirements: .PDF reader, 47.8 MB
Overview: This book explores the cutting-edge integration of Generative Artifical Intelligence (AI) techniques to enhance environmental remote sensing, providing a comprehensive guide from foundational algorithms to practical applications. It explains how advanced AI technology can be used to improve the way we monitor and understand the environment from a distance, such as through satellites or drones. It starts with an explanation of basic algorithms behind Generative AI and gradually moves to complex algorithms, showing how they can be applied to real-world environmental issues, such as tracking climate change, monitoring deforestation, and predicting natural disasters. The foundational chapters, “Introduction to Generative AI and Its Role in Remote Sensing” and “Core Concepts of Understanding Generative AI Algorithms and Models,” establish the necessary conceptual basis for a diverse audience. The former provides an overview of the fundamental principles and intuitive understanding behind generative models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models. Based on this theoretical foundation, the volume then moves into applied contexts, where specific remote sensing technologies are examined in combination with AI-based approaches.
Genre: Non-Fiction > Tech & Devices
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