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Energy Efficiency And Robustness Of Advanced Machine Learning Architectures


Energy Efficiency And Robustness Of Advanced Machine Learning Architectures
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Energy Efficiency And Robustness Of Advanced Machine Learning Architectures


Energy Efficiency And Robustness Of Advanced Machine Learning Architectures
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Author : Alberto Marchisio
language : en
Publisher: CRC Press
Release Date : 2024-11-14

Energy Efficiency And Robustness Of Advanced Machine Learning Architectures written by Alberto Marchisio and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-14 with Computers categories.


Machine Learning (ML) algorithms have shown a high level of accuracy, and applications are widely used in many systems and platforms. However, developing efficient ML-based systems requires addressing three problems: energy-efficiency, robustness, and techniques that typically focus on optimizing for a single objective/have a limited set of goals. This book tackles these challenges by exploiting the unique features of advanced ML models and investigates cross-layer concepts and techniques to engage both hardware and software-level methods to build robust and energy-efficient architectures for these advanced ML networks. More specifically, this book improves the energy efficiency of complex models like CapsNets, through a specialized flow of hardware-level designs and software-level optimizations exploiting the application-driven knowledge of these systems and the error tolerance through approximations and quantization. This book also improves the robustness of ML models, in particular for SNNs executed on neuromorphic hardware, due to their inherent cost-effective features. This book integrates multiple optimization objectives into specialized frameworks for jointly optimizing the robustness and energy efficiency of these systems. This is an important resource for students and researchers of computer and electrical engineering who are interested in developing energy efficient and robust ML. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.



Deep In Memory Architectures For Machine Learning


Deep In Memory Architectures For Machine Learning
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Author : Mingu Kang
language : en
Publisher: Springer Nature
Release Date : 2020-01-30

Deep In Memory Architectures For Machine Learning written by Mingu Kang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-30 with Technology & Engineering categories.


This book describes the recent innovation of deep in-memory architectures for realizing AI systems that operate at the edge of energy-latency-accuracy trade-offs. From first principles to lab prototypes, this book provides a comprehensive view of this emerging topic for both the practicing engineer in industry and the researcher in academia. The book is a journey into the exciting world of AI systems in hardware.



Designing Interactions With Robots


Designing Interactions With Robots
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Author : Maria Luce Lupetti
language : en
Publisher: CRC Press
Release Date : 2024-11-28

Designing Interactions With Robots written by Maria Luce Lupetti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-28 with Computers categories.


Developing robots to interact with humans is a complex interdisciplinary effort. While engineering and social science perspectives on designing human–robot interactions (HRI) are readily available, the body of knowledge and practices related to design, specifically interaction design, often remain tacit. Designing Interactions with Robots fills an important resource gap in the HRI community, and acts as a guide to navigating design-specific methods, tools, and techniques. With contributions from the field's leading experts and rising pioneers, this collection presents state of the art knowledge and a range of design methods, tools, and techniques, which cover the various phases of an HRI project. This book is accessible to an interdisciplinary audience, and does not assume any design knowledge. It provides actionable resources whose efficacy have been tested and proven in existing research. This manual is essential for HRI design students, researchers, and practitioners alike. It offers crucial guidance for the processes involved in robot and HRI design, marking a significant stride toward advancing the HRI landscape. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.



Advanced Machine Learning


Advanced Machine Learning
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Author : Dr. Amit Kumar Tyagi
language : en
Publisher: BPB Publications
Release Date : 2024-06-29

Advanced Machine Learning written by Dr. Amit Kumar Tyagi and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-29 with Computers categories.


DESCRIPTION Our book is divided into several useful concepts and techniques of machine learning. This book serves as a valuable resource for individuals seeking to deepen their understanding of advanced topics in this field. Learn about various learning algorithms, including supervised, unsupervised, and reinforcement learning, and their mathematical foundations. Discover the significance of feature engineering and selection for enhancing model performance. Understand model evaluation metrics like accuracy, precision, recall, and F1-score, along with techniques like cross-validation and grid search for model selection. Explore ensemble learning methods along with deep learning, unsupervised learning, time series analysis, and reinforcement learning techniques. Lastly, uncover real-world applications of the machine and deep learning algorithms. After reading this book, readers will gain a comprehensive understanding of machine learning fundamentals and advanced techniques. With this knowledge, readers will be equipped to tackle real-world problems, make informed decisions, and develop innovative solutions using machine and deep learning algorithms. KEY FEATURES ● Basic understanding of machine learning algorithms via MATLAB, R, and Python. ● Inclusion of examples related to real-world problems, case studies, and questions related to futuristic technologies. ● Adding futuristic technologies related to machine learning and deep learning. WHAT YOU WILL LEARN ● Ability to tackle complex machine learning problems. ● Understanding of foundations, algorithms, ethical issues, and how to implement each learning algorithm for their own use/ with their data. ● Efficient data analysis for real-time data will be understood by researchers/ students. ● Using data analysis in near future topics and cutting-edge technologies. WHO THIS BOOK IS FOR This book is ideal for students, professors, and researchers. It equips industry experts and academics with the technical know-how and practical implementations of machine learning algorithms. TABLE OF CONTENTS 1. Introduction to Machine Learning 2. Statistical Analysis 3. Linear Regression 4. Logistic Regression 5. Decision Trees 6. Random Forest 7. Rule-Based Classifiers 8. Naïve Bayesian Classifier 9. K-Nearest Neighbors Classifiers 10. Support Vector Machine 11. K-Means Clustering 12. Dimensionality Reduction 13. Association Rules Mining and FP Growth 14. Reinforcement Learning 15. Applications of ML Algorithms 16. Applications of Deep Learning 17. Advance Topics and Future Directions



Advanced Machine Learning For Cyber Attack Detection In Iot Networks


Advanced Machine Learning For Cyber Attack Detection In Iot Networks
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Author : Dinh Thai Hoang
language : en
Publisher: Academic Press
Release Date : 2025-05-12

Advanced Machine Learning For Cyber Attack Detection In Iot Networks written by Dinh Thai Hoang and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-12 with Computers categories.


Advanced Machine Learning for Cyber-Attack Detection in IoT Networks analyzes diverse machine learning techniques, including supervised, unsupervised, reinforcement, and deep learning, along with their applications in detecting and preventing cyberattacks in future IoT systems. Chapters investigate the key challenges and vulnerabilities found in IoT security, how to handle challenges in data collection and pre-processing specific to IoT environments, as well as what metrics to consider for evaluating the performance of machine learning models. Other sections look at the training, validation, and evaluation of supervised learning models and present case studies and examples that demonstrate the application of supervised learning in IoT security. - Presents a comprehensive overview of research on IoT security threats and potential attacks - Investigates machine learning techniques, their mathematical foundations, and their application in cybersecurity - Presents metrics for evaluating the performance of machine learning models as well as benchmark datasets and evaluation frameworks for assessing IoT systems



Computer Vision And Machine Intelligence For Renewable Energy Systems


Computer Vision And Machine Intelligence For Renewable Energy Systems
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Author : Ashutosh Kumar Dubey
language : en
Publisher: Elsevier
Release Date : 2024-09-20

Computer Vision And Machine Intelligence For Renewable Energy Systems written by Ashutosh Kumar Dubey and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-20 with Technology & Engineering categories.


Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source



Embedded Machine Learning For Cyber Physical Iot And Edge Computing


Embedded Machine Learning For Cyber Physical Iot And Edge Computing
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Author : Sudeep Pasricha
language : en
Publisher: Springer Nature
Release Date : 2023-10-06

Embedded Machine Learning For Cyber Physical Iot And Edge Computing written by Sudeep Pasricha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-06 with Technology & Engineering categories.


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.



Proceedings Of The International Conference On Materials Energy Environment Manufacturing Sciences Computational Intelligence And Smart Communication Meems Cisc 2024


Proceedings Of The International Conference On Materials Energy Environment Manufacturing Sciences Computational Intelligence And Smart Communication Meems Cisc 2024
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Author : Nagaraj Bhat
language : en
Publisher: Springer Nature
Release Date : 2025-07-16

Proceedings Of The International Conference On Materials Energy Environment Manufacturing Sciences Computational Intelligence And Smart Communication Meems Cisc 2024 written by Nagaraj Bhat and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-16 with Computers categories.


This is an open access book. CISC-2024 is the inaugural event in an annual series of International Conferences on Computational Intelligence and Smart Communication, organized by Shri Madhwa Vadiraja Institute of Technology and Management (SMVITM), Bantakal, Udupi, Karnataka, India. CISC-2024 aims to bring together researchers, academicians, engineers, and industry professionals to share their experiences and exchange ideas on the latest developments in the fields of soft computation, artificial intelligence systems, and smart communication. The digital revolution has profoundly impacted how people live, work, and communicate. The purpose of CISC-2024 is to discuss the role of computational intelligence in growth and the shaping of society. This international conference offers a unique opportunity to gain insights into the architecture and applications of futuristic technology across multidisciplinary areas and promote scientific growth. The International Conference on Materials, Energy, Environment & Manufacturing Sciences (MEEMS-2024) holds significant relevance in promoting sustainable practices, facilitating knowledge exchange, fostering collaborations and outreach activities. It focuses on various areas of Materials Engineering, technologies for harnessing energy sources and their utilization, environmental aspects and advances in manufacturing sciences. It emphasizes sustainable development and encourages multidisciplinary approaches to tackle challenges encountered in these areas. The conference offers networking opportunities, research dissemination and publication prospects in journals of international repute. Overall, the conference will play a crucial role in driving innovation and sustainability in Material, Energy, Environmental and Manufacturing Engineering, making it an important event for researchers and industry professionals. The conference will be held in hybrid mode, incorporating both virtual and in- person participation.



The International Conference On Advanced Machine Learning Technologies And Applications Amlta2018


The International Conference On Advanced Machine Learning Technologies And Applications Amlta2018
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2018-01-25

The International Conference On Advanced Machine Learning Technologies And Applications Amlta2018 written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-25 with Technology & Engineering categories.


This book presents the refereed proceedings of the third International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2018, held in Cairo, Egypt, on February 22–24, 2018, and organized by the Scientific Research Group in Egypt (SRGE). The papers cover current research in machine learning, big data, Internet of Things, biomedical engineering, fuzzy logic, security, and intelligence swarms and optimization.



Ai And Blockchain In Smart Grids


Ai And Blockchain In Smart Grids
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Author : Shrikant Tiwari
language : en
Publisher: CRC Press
Release Date : 2025-04-17

Ai And Blockchain In Smart Grids written by Shrikant Tiwari and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-17 with Technology & Engineering categories.


AI and Blockchain in Smart Grids: Fundamentals, Methods, and Applications examines the cutting-edge solution that combines artificial intelligence (AI), blockchain technology, and digital twin concepts to innovate the management and optimization of electrical power distribution. This innovative approach enhances the resilience, efficiency, and security of electricity grids while providing real-time insights for grid operators and stakeholders. The book covers such key elements as using: Digital twins in smart grids to gather real-time data from various grid components AI-powered analytics to process the data generated by digital twins and to analyze this information to detect patterns, predict grid failures, and recommend adjustments to enhance a grid's performance Blockchain-based security to ensure the secure and transparent management of data within a smart grid, especially a tamper-resistant ledger to store information related to energy production, distribution, and consumption Decentralized data sharing to allow grid data to be shared securely among various stakeholders, including utilities, regulators, and consumers Grid optimization techniques to improve electricity distribution, reduce energy waste, and balance supply and demand efficiently Select real-world case studies and practical examples demonstrate how AI and blockchain are currently being applied to enhance grid management, energy distribution, and sustainability. By explaining to researchers, academics, and students how AI and blockchain can revolutionize electricity distribution and make grids smarter, more secure, and environmentally friendly, the book points to a future where grid operators, regulators, and consumers will benefit from real-time data and a resilient, efficient energy ecosystem.