As artificial intelligence (AI) processing moves from the cloud to the edge of the network, battery-powered and deeply embedded devices are challenged to perform AI functions such as computer vision and voice recognition. Microchip Technology Inc., via its Silicon Storage Technology (SST) subsidiary, is addressing this challenge by significantly reducing power with its analog memory technology, the memBrain Memory Solution. The memBrain solution is being adopted by today's companies looking to advance machine learning capacities in edge devices. Due to its ability to significantly reduce power, this analog in-memory computer solution is ideal for an AI application. Neuromorphic Computing Systems for Industry 4.0 covers the available literature in the field of neural computing-based microchip technology. It provides further research opportunities in this dynamic field. Covering topics such as emotion recognition, biometric authentication, and neural network protection, this premier reference source is an essential resource for technology developers, computer scientists, engineers, students and educators of higher education, librarians, researchers, and academicians.
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K. Martin Sagayam received his PhD in Electronics and Communication Engineering (Signal image processing using machine learning algorithms) from Karunya University. He received Master of Engineering in Communication Systems from Anna University, Chennai and received Bachelor of Enigeering in Electronics and Communication Engineering from Anna University. Currently, he is working as Assistant Professor in the Department of ECE, Karunya Institute Technology and Sciences, Coimbatore, India. He has authored/ co-authored more than 30 referred International Journals. He has also presented more than 20 papers in reputed international and national conferences. He has authored 10 book chapters with reputed international publishers like Elsevier, Springer, IGI Global and CRC press. He has editor in the reputed book and book series with reputed international publishers like IGI Global, and CRC Press. He has reviewed research articles from the journal of Signal, Image and Video Processing, Intelligent Decision Technologies, International Journal of Engineering Research & Technology, Pattern analysis and its applications and Informing Science Institute. He is an active member of professional bodies such as Engineering and Scientific Research Groups, International Society of Promising Computer Engineers, Copernicus, Scientific Engineering Research Corporation, International Association of Computer Science and Information Technology, International Association of Engineers, Indian Society of Electronics and Communication Engineering and Orcid. His area of interest includes Communication systems, signal and image processing, machine learning and virtual reality.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardback. Etat : New. As artificial intelligence (AI) processing moves from the cloud to the edge of the network, battery-powered and deeply embedded devices are challenged to perform AI functions such as computer vision and voice recognition. Microchip Technology Inc., via its Silicon Storage Technology (SST) subsidiary, is addressing this challenge by significantly reducing power with its analog memory technology, the memBrain Memory Solution. The memBrain solution is being adopted by today's companies looking to advance machine learning capacities in edge devices. Due to its ability to significantly reduce power, this analog in-memory computer solution is ideal for an AI application. Neuromorphic Computing Systems for Industry 4.0 covers the available literature in the field of neural computing-based microchip technology. It provides further research opportunities in this dynamic field. Covering topics such as emotion recognition, biometric authentication, and neural network protection, this premier reference source is an essential resource for technology developers, computer scientists, engineers, students and educators of higher education, librarians, researchers, and academicians. N° de réf. du vendeur LU-9781668465967
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