Brain-Computer Interface

Name: Brain-Computer Interface
Brand: Unknown
SKU: 9781119857204
Price: 371.99 NZD
Availability: InStock

Using Deep Learning Applications

0.0 (0 reviews)

Summary

This book explores the fascinating intersection of neuroscience and computer technology, detailing how brain-computer interfaces can interpret neurological signs to communicate with external devices. It delves into both the current research and the potential future applications of this technology, offering insights into how machines can be controlled using our thoughts. By examining the implications for society and individuals, it showcases the diverse fields impacted by advancements in this cutting-edge science.
Read More

Format: Hardback

$371⁹⁹

AVAILABLE WITH SUPPLIER Ships from our Auckland warehouse within 3-4 weeks

Found a better price? Request a price match

Brain-Computer Interface

$371⁹⁹

Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?

This book may appeal to you if you're fascinated by the intersection of neuroscience and technology and want to explore how our minds can directly communicate with computers. It delves into the latest advancements in brain-computer interface technology, making it ideal for tech enthusiasts interested in innovative concepts and future possibilities in computing.

Brain-Computer Interface

Description

Brain-Computer Interface

It covers all the research prospects and recent advancements in the brain-computer interface using deep learning.

The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world. For example, creating communication or control applications for locked-in patients who have no control over their bodies will be one such use. Recently, from communication to marketing, recovery, care, mental state monitoring, and entertainment, the possible application areas have been expanding.

Machine learning algorithms have advanced BCI technology in the last few decades, and in the sense of classification accuracy, performance standards have been greatly improved. For BCI to be effective in the real world, however, some problems remain to be solved.

Research focusing on deep learning is anticipated to bring solutions in this regard. Deep learning has been applied in various fields such as computer vision and natural language processing, along with BCI growth, outperforming conventional approaches to machine learning. As a result, a significant number of researchers have shown interest in deep learning in engineering, technology, and other industries; convolutional neural network (CNN), recurrent neural network (RNN), and generative adversarial network (GAN).

Audience

Researchers and industrialists working in brain-computer interface, deep learning, machine learning, medical image processing, data scientists and analysts, machine learning engineers, electrical engineering, and information technologists.

Book Details

INFORMATION

ISBN: 9781119857204

Publisher: John Wiley & Sons Inc

Format: Hardback

Date Published: 28 February 2023

Country: United States

Imprint: Wiley-Scrivener

Contributors:

Edited by Balamurugan Balusamy
Edited by Rajesh Kumar Dhanaraj
Edited by M. G. Sumithra
Edited by Mariofanna Milanova
Edited by Chandran Venkatesan
Edited by Rajesh Kumar Dhanaraj
Edited by Balamurugan Balusamy

Audience: Professional and scholarly

DIMENSIONS

Weight: 703g

Pages: 320

Collections

Computing & Technology Education & Reference Non-Fiction

About the Author

M. G. Sumithra, PhD, is a professor at Anna University Chennai, India. With 25 years of teaching experience, she has published more than 70 technical papers in refereed journals, 3 book chapters, and 130 research papers in national and international conferences. She is a Nvidia Deep Learning Institute Certified Instructor for "Computer Vision".

Rajesh Kumar Dhanaraj, PhD, is a professor in the School of Computing Science and Engineering at Galgotias University, Greater Noida, India. He has contributed around 25 authored and edited books on various technologies, 17 patents, and more than 40 articles and papers in various refereed journals and international conferences. He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).

Mariofanna Milanova, PhD, is a professor in the Department of Computer Science at the University of Arkansas, Little Rock, USA. She is an IEEE Senior Member and Nvidia’s Deep Learning Institute University Ambassador. She has published more than 120 publications, more than 53 journal papers, 35 book chapters, and numerous conference papers. She also has two patents.

Balamurugan Balusamy, PhD, is a professor in the School of Computing Science and Engineering, Galgotias University, Greater Noida, India. He is a Pioneer Researcher in the areas of big data and IoT and has published more than 70 articles in various top international journals.

V. Chandran holds an M.E degree in VLSI Design from Government College of Technology, Coimbatore, and is a Nvidia Certified Instructor for Deep learning for Computer Vision.