Embedded Machine Learning With Microcontrollers: Applications on Stm32 Development Boards - Rilegato

Nsalan, Cem; Hke, Berkan; Atmaca, Eren

Rilegato

ISBN 10: 303170911X ISBN 13: 9783031709111

Casa editrice: Springer-Nature New York Inc, 2024

Riassunto

This textbook introduces basic embedded machine learning methods by exploring practical applications on STM32 development boards. Covering traditional and neural network-based machine learning methods implemented on microcontrollers, the text is designed for use in courses on microcontrollers, microprocessor systems, and embedded systems. Following the learning by doing approach, the book will enable students to grasp embedded machine learning concepts through real-world examples that will provide them with the design and implementation skills needed for a competitive job market. By utilizing a programming environment that enables students to reach and modify low-level microcontroller properties, the material allows for more control of the developed system. Students will be guided in implementing machine learning methods to be deployed and tested on microcontrollers throughout the book, with the theory behind the implemented methods also emphasized. Sample codes and course slides are available for readers and instructors, and a solutions manual is available to instructors. The book will also be an ideal reference for practicing engineers and electronics hobbyists.

Su questo libro

Informazioni sull?autore

Cem Ünsalan is a full professor at the Department of Electrical and Electronics Engineering at Yeditepe University, Turkey, since 2013. He is the Dean of the Faculty of Engineering at the same university. Dr. Ünsalan also worked as a full professor at the Department of Electrical and Electronics Engineering at Marmara University, Turkey,  between 2017 and 2023. He served as the department head for four years there. Dr. Ünsalan received his BSc degree from Hacettepe University, Turkey, his MSc degree from Bogazici University, Turkey, and his Ph.D. from The Ohio State University, USA, in 1995, 1998, and 2003, respectively. His research focuses on embedded systems, computer vision, and remote sensing. He has published extensively on these topics in respected journals and has written several books, including Embedded System Design with ARM Cortex-M Microcontrollers: Applications with C, C++ and MicroPython (Springer, 2022).

Berkan Höke is currently working as a senior machine vision engineer at Agsenze Ltd, United Kingdom. He has a diverse professional background including roles as a computer vision engineer at Migros, Turkey (2017–2020), machine learning engineer at Huawei, Turkey (2020–2022), and computer vision engineer at Techsign, Turkey (2022–2023). Mr. Höke received his BSc degree from Bilkent University, Turkey, and his MSc degree from Bogaziçi University, Turkey, in 2014 and 2019, respectively. His research focuses on machine learning, computer vision, and embedded systems.

Eren Atmaca is currently pursuing his master’s degree in communications and electronics engineering at Technical University of Munich, Germany. He received his bachelor's degree from Marmara University, Turkey in 2022. His research focuses on embedded systems, signal processing, and machine learning.

 

Dalla quarta di copertina

This textbook introduces basic and advanced embedded machine learning methods by exploring practical applications on STM32 development boards. By covering traditional and neural network-based machine learning methods implemented on microcontrollers, the text is designed for use in courses on microcontrollers and embedded machine learning systems. Following the learning-by-doing approach, the book will enable students to grasp embedded machine learning concepts through real-world examples, providing them with the design and implementation skills needed for a competitive job market. By utilizing a programming environment that enables students to reach and modify low-level microcontroller properties, the material allows for more control of the developed system. Students are guided in implementing machine learning methods to be deployed and tested on microcontrollers throughout the book, with the theory behind the implemented methods also emphasized. Sample codes and real-world projects are available for readers and instructors. The book will also be an ideal reference for practicing engineers and electronics hobbyists.

• Teaches the embedded system design skills needed for today’s job market;
• Thoroughly explains each concept and provides illustrated examples and projects;
• Includes sample codes and course slides and a solutions manual.

Dettagli dell?edizione

• Editore: Springer-Nature New York Inc
• Data di pubblicazione: 2024
• ISBN 10: 303170911X
• ISBN 13: 9783031709111
• Rilegatura: Copertina rigida
• Lingua: Inglese
• Numero di pagine: 400
• Contatto del produttore: non disponibile