Intel OpenVino: A Must-Know Deep Learning Toolkit

This chapter is dedicated to learning about the OpenVino tool by Intel. The chapter gives a basic introduction of OpenVino and proceeds with detailed explanations of installation and setup. Next it touches upon some sample applications wherein we can make use of OpenVino. It can be widely used for c...

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Hauptverfasser: Vasudevan, Shriram K., Pulari, Sini Raj, Vasudevan, Subashri
Format: Buchkapitel
Sprache:eng
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Zusammenfassung:This chapter is dedicated to learning about the OpenVino tool by Intel. The chapter gives a basic introduction of OpenVino and proceeds with detailed explanations of installation and setup. Next it touches upon some sample applications wherein we can make use of OpenVino. It can be widely used for classification problems and identification problems. Also, it shows the screenshots of execution results of "Emotion detection problem," where OpenVino is utilized to detect the emotion of a person in real time. Finally, the chapter summarizes key points to note and offers useful links for further reading, along with a quiz. This chapter helps the readers to learn about the OpenVino tool by Intel. It gives a basic introduction of OpenVino and proceeds with detailed explanations of installation and setup. The chapter touches upon some sample applications wherein people can make use of OpenVino. OpenVino can be widely used for classification problems and identification problems. The chapter shows the screenshots of execution results of "Emotion detection problem", where OpenVino is utilized to detect the emotion of a person in real time. OpenVino provides improved neural network performance. One can say, for sure that OpenVino is cost-effective and most suitable for real-time computer vision applications. Also, OpenVino enables Deep Learning Inference and Heterogeneous execution a reality. OpenVino also can really enable the developers to innovate with the Deep Learning and Artificial Intelligence solutions. OpenVino is compatible with Linux/Windows 10/MAC.
DOI:10.1201/9781003185635-11