UID:
almahu_9949420159902882
Format:
XVII, 914 p. 513 illus., 393 illus. in color.
,
online resource.
Edition:
1st ed. 2023.
ISBN:
9789811960048
Series Statement:
Algorithms for Intelligent Systems,
Content:
The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2021), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during July 6-7, 2022. This book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.
Note:
Modelling Muller Lyer Illusion Using Information Geometry -- Building up a Categorical Sentiment Dictionary for Tourism Destination Policy Evaluation -- Statistical Analysis of Stress Prediction from Speech Signatures -- DermoCare.AI: A Skin Lesion Detection System using Deep Learning Concepts -- Analysis of Phishing Base Problems using Random Forest Features Selection Techniques and Machine Learning Classifiers -- Cost Prediction for Online Home-Based Application Services by Using Linear Regression Techniques -- Convolutional neural network-based intrusion detection system and predict the DDoS attack -- BERT Transformer based Fake News Detection in Twitter Social Media -- The Facial Expression Recognition Using Deep Neural Network -- New IoT Based Portable Microscopic Somatic Cell Count Analysis.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9789811960031
Additional Edition:
Printed edition: ISBN 9789811960055
Additional Edition:
Printed edition: ISBN 9789811960062
Language:
English
DOI:
10.1007/978-981-19-6004-8
URL:
https://doi.org/10.1007/978-981-19-6004-8
URL:
Volltext
(URL des Erstveröffentlichers)
