Embedded Artificial Intelligence by Arpita Nath Boruah (.ePUB)+

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File Size: 19.5 MB

Embedded Artificial Intelligence: Real-Life Applications and Case Studies by Arpita Nath Boruah, Mrinal Goswami, Manoj Kumar, Octavio Loyola-González
Requirements: .ePUB, .PDF reader, 19.5 MB
Overview: This book explores the role of embedded AI in revolutionizing industries such as healthcare, transportation, manufacturing, and retail. It begins by introducing the fundamentals of AI and embedded systems and specific challenges and opportunities. A key focus of this book is developing efficient and effective algorithms and models for embedded AI systems, as embedded systems have limited processing power, memory, and storage. It discusses a variety of techniques for optimizing algorithms and models for embedded systems, including hardware acceleration, model compression, and quantization. Embedded systems, which are distinguished by their small footprint, restricted resources, and ability to operate in real time, are progressively evolving into centres of intelligence by incorporating Machine Learning algorithms. This reference book is for students, researchers, and professionals interested in embedded AI and relevant branches of Computer Science, electrical engineering, or Artificial Intelligence.
Genre: Non-Fiction > Tech & Devices

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