UID:
almahu_9949552645202882
Umfang:
XXXIII, 741 p. 323 illus., 255 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2023.
ISBN:
9789819937349
Serie:
Lecture Notes in Networks and Systems, 725
Inhalt:
This book features high-quality research papers presented at the 5th International Conference on Computational Intelligence in Pattern Recognition (CIPR 2023), held at Department of Computer Science and Engineering, Techno Main Salt Lake, West Bengal, India, during May 27-28, 2023. It includes practical development experiences in various areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics, and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.
Anmerkung:
A New Technique of Cipher Type Identification using Convolutional Neural Networks -- Monthly Rainfall forecasting Using Sequential Models -- Detection and Classification of Dental Caries Using Deep and Transfer Learning -- Method Level Code Smells Detection Using Machine Learning Models -- Performance Investıgatıon of Svm and Modıfıed Svm Algorıthms for Acute Health Dıagnosıs -- An Efficient Multifactor Authentication System -- A CNN based approach for Face Recognition under dif-ferent orientations -- A Deep Learning Approach for Detection of Disease in Plant Leaves -- Label Consistency based Modified Sequential Dictionary Learning based Approach for PIR Sensor based Detection of Human Movement Direction -- Machine Learning Based Phishing Detection in Heterogeneous Information Network.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9789819937332
Weitere Ausg.:
Printed edition: ISBN 9789819937356
Sprache:
Englisch
DOI:
10.1007/978-981-99-3734-9
URL:
https://doi.org/10.1007/978-981-99-3734-9
URL:
Volltext
(URL des Erstveröffentlichers)
