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Modern approaches in machine learning and cognitive science = a walkthrough.. Volume 4 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modern approaches in machine learning and cognitive science/ edited by Vinit Kumar Gunjan, Jacek M. Zurada, Ninni Singh.
其他題名:	a walkthrough.
其他作者:	Gunjan, Vinit Kumar.
出版者:	Cham :Springer International Publishing : : 2024.,
面頁冊數:	vii, 342 p. :ill., digital ;24 cm.
內容註:	Effect of Social Networking Advertisements (SNAs) On Attitudes and Purchase Intention towards Brand Products -- Design of Optimal Waste Management System using IOT and Machine Learning Technique in Educational institutions -- An enhanced Woelfel Image Noise Filter -- PAPR and SER Performance Analysis of OFDMA and SCFDMA -- VLSI Implementation of an 8051 Microcontroller using VHDL and Re- corrective Measure using AI -- A survey of Internet of Things frameworks for crowd management system.
Contained By:	Springer Nature eBook
標題:	Machine learning. -
電子資源:	https://doi.org/10.1007/978-3-031-43009-1
ISBN:	9783031430091

Modern approaches in machine learning and cognitive science = a walkthrough.. Volume 4 /
Modern approaches in machine learning and cognitive sciencea walkthrough.Volume 4 /[electronic resource] :edited by Vinit Kumar Gunjan, Jacek M. Zurada, Ninni Singh. - Cham :Springer International Publishing :2024. - vii, 342 p. :ill., digital ;24 cm. - Studies in computational intelligence,v. 11171860-9503 ;. - Studies in computational intelligence ;v. 1117..

Effect of Social Networking Advertisements (SNAs) On Attitudes and Purchase Intention towards Brand Products -- Design of Optimal Waste Management System using IOT and Machine Learning Technique in Educational institutions -- An enhanced Woelfel Image Noise Filter -- PAPR and SER Performance Analysis of OFDMA and SCFDMA -- VLSI Implementation of an 8051 Microcontroller using VHDL and Re- corrective Measure using AI -- A survey of Internet of Things frameworks for crowd management system.

This book provides a systematic and comprehensive overview of cognitive intelligence and AI-enabled IoT ecosystem and machine learning, capable of recognizing the object pattern in complex and large data sets. A remarkable success has been experienced in the last decade by emulating the brain-computer interface. It presents the applied cognitive science methods and AI-enabled technologies that have played a vital role at the core of practical solutions for a wide scope of tasks between handheld apps and industrial process control, autonomous vehicles, IoT, intelligent learning environment, game theory, human computer interaction, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The book contains contents highlighting artificial neural networks that are analogous to the networks of neurons that comprise the brain and have given computers the ability to distinguish an image of a cat from one of a coconut, to spot pedestrians with enough accuracy to direct a self-driving car, and to recognize and respond to the spoken word. The chapters in this book focus on audiences interested in artificial intelligence, machine learning, fuzzy, cognitive and neurofuzzy-inspired computational systems, their theories, mechanisms, and architecture, which underline human and animal behavior, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step execution and explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions on applications of machine learning, artificial intelligence, and cognitive science such as healthcare products, AI-enabled IoT, gaming, medical, and engineering. Overall, this book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and academics in the field of machine learning and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.

ISBN: 9783031430091

Standard No.: 10.1007/978-3-031-43009-1doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

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