Embedded Deep Learning
Download Embedded Deep Learning full books in PDF, epub, and Kindle. Read online free Embedded Deep Learning ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Bert Moons |
| Publisher | : Springer |
| Total Pages | : 206 |
| Release | : 2018-10-23 |
| Genre | : Technology & Engineering |
| ISBN | : 3319992236 |
This book covers algorithmic and hardware implementation techniques to enable embedded deep learning. The authors describe synergetic design approaches on the application-, algorithmic-, computer architecture-, and circuit-level that will help in achieving the goal of reducing the computational cost of deep learning algorithms. The impact of these techniques is displayed in four silicon prototypes for embedded deep learning. Gives a wide overview of a series of effective solutions for energy-efficient neural networks on battery constrained wearable devices; Discusses the optimization of neural networks for embedded deployment on all levels of the design hierarchy – applications, algorithms, hardware architectures, and circuits – supported by real silicon prototypes; Elaborates on how to design efficient Convolutional Neural Network processors, exploiting parallelism and data-reuse, sparse operations, and low-precision computations; Supports the introduced theory and design concepts by four real silicon prototypes. The physical realization’s implementation and achieved performances are discussed elaborately to illustrated and highlight the introduced cross-layer design concepts.
| Author | : Pete Warden |
| Publisher | : O'Reilly Media |
| Total Pages | : 504 |
| Release | : 2019-12-16 |
| Genre | : Computers |
| ISBN | : 1492052019 |
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
| Author | : Yifeng Zhu |
| Publisher | : |
| Total Pages | : 736 |
| Release | : 2017-07 |
| Genre | : Computers |
| ISBN | : 9780982692660 |
This book introduces basic programming of ARM Cortex chips in assembly language and the fundamentals of embedded system design. It presents data representations, assembly instruction syntax, implementing basic controls of C language at the assembly level, and instruction encoding and decoding. The book also covers many advanced components of embedded systems, such as software and hardware interrupts, general purpose I/O, LCD driver, keypad interaction, real-time clock, stepper motor control, PWM input and output, digital input capture, direct memory access (DMA), digital and analog conversion, and serial communication (USART, I2C, SPI, and USB).
| Author | : Donald J. Norris |
| Publisher | : Apress |
| Total Pages | : 379 |
| Release | : 2017-06-05 |
| Genre | : Computers |
| ISBN | : 1484227433 |
Gain a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform. Most of the major AI topics will be explored, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more! AI in action will be demonstrated using the Python language on the Raspberry Pi. The Prolog language will also be introduced and used to demonstrate fundamental AI concepts. In addition, the Wolfram language will be used as part of the deep machine learning demonstrations. A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. Minimal expense is needed for the projects as only a few sensors and actuators will be required. Beginners and hobbyists can jump right in to creating AI projects with the Raspberry PI using this book. What You'll Learn What AI is and—as importantly—what it is not Inference and expert systems Machine learning both shallow and deep Fuzzy logic and how to apply to an actual control system When AI might be appropriate to include in a system Constraints and limitations of the Raspberry Pi AI implementation Who This Book Is For Hobbyists, makers, engineers involved in designing autonomous systems and wanting to gain an education in fundamental AI concepts, and non-technical readers who want to understand what AI is and how it might affect their lives.
| Author | : Vikrant Bhateja |
| Publisher | : Springer Nature |
| Total Pages | : 880 |
| Release | : 2020-04-07 |
| Genre | : Technology & Engineering |
| ISBN | : 9811509476 |
This book gathers selected research papers presented at the First International Conference on Embedded Systems and Artificial Intelligence (ESAI 2019), held at Sidi Mohamed Ben Abdellah University, Fez, Morocco, on 2–3 May 2019. Highlighting the latest innovations in Computer Science, Artificial Intelligence, Information Technologies, and Embedded Systems, the respective papers will encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.
| Author | : Sudeep Pasricha |
| Publisher | : Springer Nature |
| Total Pages | : 481 |
| Release | : 2023-10-09 |
| Genre | : Technology & Engineering |
| ISBN | : 3031399323 |
This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.
| Author | : Elecia White |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 329 |
| Release | : 2011-10-25 |
| Genre | : Computers |
| ISBN | : 1449320589 |
Interested in developing embedded systems? Since they donâ??t tolerate inefficiency, these systems require a disciplined approach to programming. This easy-to-read guide helps you cultivate a host of good development practices, based on classic software design patterns and new patterns unique to embedded programming. Learn how to build system architecture for processors, not operating systems, and discover specific techniques for dealing with hardware difficulties and manufacturing requirements. Written by an expert whoâ??s created embedded systems ranging from urban surveillance and DNA scanners to childrenâ??s toys, this book is ideal for intermediate and experienced programmers, no matter what platform you use. Optimize your system to reduce cost and increase performance Develop an architecture that makes your software robust in resource-constrained environments Explore sensors, motors, and other I/O devices Do more with less: reduce RAM consumption, code space, processor cycles, and power consumption Learn how to update embedded code directly in the processor Discover how to implement complex mathematics on small processors Understand what interviewers look for when you apply for an embedded systems job "Making Embedded Systems is the book for a C programmer who wants to enter the fun (and lucrative) world of embedded systems. Itâ??s very well writtenâ??entertaining, evenâ??and filled with clear illustrations." â??Jack Ganssle, author and embedded system expert.
| Author | : Ivan Morgillo |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 282 |
| Release | : 2016-07-29 |
| Genre | : Computers |
| ISBN | : 1785283286 |
Create the perfectly customized system by unleashing the power of Android OS on your embedded device About This Book Understand the system architecture and how the source code is organized Explore the power of Android and customize the build system Build a fully customized Android version as per your requirements Who This Book Is For If you are a Java programmer who wants to customize, build, and deploy your own Android version using embedded programming, then this book is for you. What You Will Learn Master Android architecture and system design Obtain source code and understand the modular organization Customize and build your first system image for the Android emulator Level up and build your own Android system for a real-world device Use Android as a home automation and entertainment system Tailor your system with optimizations and add-ons Reach for the stars: look at the Internet of Things, entertainment, and domotics In Detail Take a deep dive into the Android build system and its customization with Learning Embedded Android Programming, written to help you master the steep learning curve of working with embedded Android. Start by exploring the basics of Android OS, discover Google's “repo” system, and discover how to retrieve AOSP source code. You'll then find out to set up the build environment and the first AOSP system. Next, learn how to customize the boot sequence with a new animation, and use an Android “kitchen” to “cook” your custom ROM. By the end of the book, you'll be able to build customized Android open source projects by developing your own set of features. Style and approach This step-by-step guide is packed with various real-world examples to help you create a fully customized Android system with the most useful features available.
| Author | : Ovidiu Vermesan |
| Publisher | : CRC Press |
| Total Pages | : 143 |
| Release | : 2023-05-05 |
| Genre | : Computers |
| ISBN | : 1000881911 |
Recent technological developments in sensors, edge computing, connectivity, and artificial intelligence (AI) technologies have accelerated the integration of data analysis based on embedded AI capabilities into resource-constrained, energy-efficient hardware devices for processing information at the network edge. Embedded AI combines embedded machine learning (ML) and deep learning (DL) based on neural networks (NN) architectures such as convolutional NN (CNN), or spiking neural network (SNN) and algorithms on edge devices and implements edge computing capabilities that enable data processing and analysis without optimised connectivity and integration, allowing users to access data from various sources. Embedded AI efficiently implements edge computing and AI processes on resource-constrained devices to mitigate downtime and service latency, and it successfully merges AI processes as a pivotal component in edge computing and embedded system devices. Embedded AI also enables users to reduce costs, communication, and processing time by assembling data and by supporting user requirements without the need for continuous interaction with physical locations. This book provides an overview of the latest research results and activities in industrial embedded AI technologies and applications, based on close cooperation between three large-scale ECSEL JU projects, AI4DI, ANDANTE, and TEMPO. The book’s content targets researchers, designers, developers, academics, post-graduate students and practitioners seeking recent research on embedded AI. It combines the latest developments in embedded AI, addressing methodologies, tools, and techniques to offer insight into technological trends and their use across different industries.
| Author | : Chen Chi Hau |
| Publisher | : World Scientific |
| Total Pages | : 404 |
| Release | : 2020-04-04 |
| Genre | : Computers |
| ISBN | : 9811211086 |
