Embedded Vision: An Introduction
- 9h 37m
- S. Muruganand, S. R. Vijayalakshmi
- Mercury Learning
- 2020
Embedded vision is the integration of “computer vision” into machines that use algorithms to decode meaning from observed images or video. It has a wide range of applications to machine learning, artificial intelligence, industrial, medical, driverless cars, drones, smart phones, aerospace, defense, agriculture, consumer, surveillance, robotics and security. This book is an introductory guide for anyone who is interested in designing machines that have vision-enabled, embedded products. It covers a large number of topics encountered in hardware architecture, software algorithms, applications, advancements in camera, processors, and sensors in the field of embedded vision.
Features:
- Includes a wide range of applications to artificial intelligence, machine learning, industry, science, medicine, transportation, civil infrastructure, and security
- Covers a large number of topics encountered in hardware architecture, software algorithms, applications, advancements in processors and sensors.
About the Authors
S. R. Vijayalakshmi is a university professor and researcher who teaches courses in wireless communication and engineering. Vijayalakshmi and Muruganand are the authors of Wireless Sensor Networks; Ocean Instrumentation, Electronics, and Energy; and Embedded Vision: An Introduction (published by Mercury Learning and Information).
S. Muruganand is a university professor and researcher who teaches courses in wireless communication and engineering. Muruganand and Vijayalakshmi are the authors of Wireless Sensor Networks; Ocean Instrumentation, Electronics, and Energy; and Embedded Vision: An Introduction (published by Mercury Learning and Information).
In this Book
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Embedded Vision
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Industrial Vision
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Medical Vision
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Video Analytics
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Digital Image Processing
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Camera—Image Sensor
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Embedded Vision Processors and Sensors
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Computer Vision
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Artificial Intelligence for Embedded Vision
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Vision-Based Real-Time Examples
