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020 _a9781032766607
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037 _bTaylor & Francis
_cGBP 155.00
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040 _a01
041 _aeng
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100 1 _aArpita Nath Boruah
_9399
245 1 0 _aEmbedded Artificial Intelligence
_bReal-Life Applications and Case Studies
250 _a1
260 _bChapman and Hall/CRC
_c20250327
300 _a310 p
520 _bThis 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. Key features: Explores security experiments in emerging post‑CMOS technologies using AI, including side channel attack‑resistant embedded systems Discusses different hardware and software platforms available for developing embedded AI applications, as well as the various techniques used to design and implement these systems Considers ethical and societal implications of embedded AI vis‑a‑vis the need for responsible development and deployment of embedded AI systems Focuses on application‑based research and case studies to develop embedded AI systems for real‑life applications Examines high‑end parallel systems to run complex AI algorithms and comprehensive functionality while maintaining portability and power efficiency This reference book is for students, researchers, and professionals interested in embedded AI and relevant branches of computer science, electrical engineering, or artificial intelligence.
700 1 _aMrinal Goswami
_4B01
_9400
700 1 _aManoj Kumar
_4B01
_9401
700 1 _aOctavio Loyola-González
_4B01
_9402
999 _c10287
_d10287