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Bio-inspired Neurocomputing / edited by Akash Kumar Bhoi, Pradeep Kumar Mallick, Chuan-Ming Liu, Valentina E. Balas.

Springer Nature - Springer Intelligent Technologies and Robotics eBooks 2021 English International Available online

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Format:
Book
Contributor:
Bhoi, Akash Kumar., Editor.
Mallick, Pradeep Kumar., Editor.
Liu, Chuan-Ming., Editor.
Balas, Valentina E., Editor.
Series:
Studies in Computational Intelligence, 1860-9503 ; 903
Language:
English
Subjects (All):
Computational intelligence.
Image processing--Digital techniques.
Image processing.
Computer vision.
Neurosciences.
Machine learning.
Neural networks (Computer science).
Computational Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Neuroscience.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Local Subjects:
Computational Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Neuroscience.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Physical Description:
1 online resource (427 pages) : illustrations
Edition:
1st ed. 2021.
Place of Publication:
Singapore : Springer Nature Singapore : Imprint: Springer, 2021.
Summary:
This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchers as well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.
Contents:
Performance Measurement of various Hybridized kernels for Noise Normalization
A precise analysis of Deep Learning for Medical Image Processing
Artificial Intelligence for Internet of Things
A Brief Review on Brain Tumour Detection
Deep Learning Techniques for Electronic Health
A Review on Psychological Brainwaves Behavior.
ISBN:
981-15-5495-1

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