Near Memory And In Memory Computing Designs For Keyword Spotting And Object Detection PDF Download

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TinyML

TinyML
Author: Pete Warden
Publisher: O'Reilly Media
Total Pages: 504
Release: 2019-12-16
Genre: Computers
ISBN: 1492052019

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Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size


Hardware for Artificial Intelligence

Hardware for Artificial Intelligence
Author: Alexantrou Serb
Publisher: Frontiers Media SA
Total Pages: 229
Release: 2022-09-26
Genre: Science
ISBN: 2889763986

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Analog Circuits for Machine Learning, Current/Voltage/Temperature Sensors, and High-speed Communication

Analog Circuits for Machine Learning, Current/Voltage/Temperature Sensors, and High-speed Communication
Author: Pieter Harpe
Publisher: Springer Nature
Total Pages: 351
Release: 2022-03-24
Genre: Technology & Engineering
ISBN: 303091741X

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This book is based on the 18 tutorials presented during the 29th workshop on Advances in Analog Circuit Design. Expert designers present readers with information about a variety of topics at the frontier of analog circuit design, with specific contributions focusing on analog circuits for machine learning, current/voltage/temperature sensors, and high-speed communication via wireless, wireline, or optical links. This book serves as a valuable reference to the state-of-the-art, for anyone involved in analog circuit research and development.


Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning

Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning
Author: Vikram Jain
Publisher: Springer Nature
Total Pages: 199
Release: 2023-09-15
Genre: Technology & Engineering
ISBN: 3031382307

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This book explores and motivates the need for building homogeneous and heterogeneous multi-core systems for machine learning to enable flexibility and energy-efficiency. Coverage focuses on a key aspect of the challenges of (extreme-)edge-computing, i.e., design of energy-efficient and flexible hardware architectures, and hardware-software co-optimization strategies to enable early design space exploration of hardware architectures. The authors investigate possible design solutions for building single-core specialized hardware accelerators for machine learning and motivates the need for building homogeneous and heterogeneous multi-core systems to enable flexibility and energy-efficiency. The advantages of scaling to heterogeneous multi-core systems are shown through the implementation of multiple test chips and architectural optimizations.


ECAI 2023

ECAI 2023
Author: K. Gal
Publisher: IOS Press
Total Pages: 3328
Release: 2023-10-18
Genre: Computers
ISBN: 164368437X

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Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.


Efficient Processing of Deep Neural Networks

Efficient Processing of Deep Neural Networks
Author: Vivienne Sze
Publisher: Springer Nature
Total Pages: 254
Release: 2022-05-31
Genre: Technology & Engineering
ISBN: 3031017668

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This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.


Masters Theses in the Pure and Applied Sciences

Masters Theses in the Pure and Applied Sciences
Author: Wade H. Shafer
Publisher: Springer Science & Business Media
Total Pages: 391
Release: 2012-12-06
Genre: Science
ISBN: 1461524539

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Masters Theses in the Pure and Applied Sciences was first conceived, published, and disseminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS)* at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dis semination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the though that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all concerned if the printing and distribution of the volumes were handled by an international publishing house to assure improved service and broader dissemi nation. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Corporation of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 37 (thesis year 1992) a total of 12,549 thesis titles from 25 Canadian and 153 United States universities. We are sure that this broader base for these titles reported will greatly enhance the value of this impor tant annual reference work. While Volume 37 reports theses submitted in 1992, on occasion, certain uni versities do report theses submitted in previous years but not reported at the time.


Science Abstracts

Science Abstracts
Author:
Publisher:
Total Pages: 948
Release: 1993
Genre: Electrical engineering
ISBN:

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Low-Power Computer Vision

Low-Power Computer Vision
Author: George K. Thiruvathukal
Publisher: CRC Press
Total Pages: 395
Release: 2022-02-22
Genre: Computers
ISBN: 1000540960

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Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015. The winners share their solutions and provide insight on how to improve the efficiency of machine learning systems.