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Pattern recognition and data analysis with applications / Deepak Gupta, Rajat Subhra Goswami, Subhasish Banerjee, M. Tanveer, Ram Bilas Pachori, editors.

Gupta, Deepak, editor.; Goswami, Rajat Subhra, editor.; Banerjee, Subhasish, editor.; Tanveer, M., editor.; Pachori, Ram Bilas, 1979- editor.
2022
TK7882.P3
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Title
Pattern recognition and data analysis with applications / Deepak Gupta, Rajat Subhra Goswami, Subhasish Banerjee, M. Tanveer, Ram Bilas Pachori, editors.
ISBN
9789811915208 (electronic bk.)
9811915202 (electronic bk.)
9811915199
9789811915192
DOI
https://doi.org/10.1007/978-981-19-1520-8
Published
Singapore : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource (xvi, 835 pages) : illustrations (some color).
Item Number
10.1007/978-981-19-1520-8 doi
Call Number
TK7882.P3
Dewey Decimal Classification
006.4
Summary
This book covers latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing and their applications in real world. The topics covered in machine learning involves feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN) and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modelling from video, 3D object recognition, localization and tracking, medical image analysis and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multi-task, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG) and electromyogram (EMG). .
Note
Includes author index.
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Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Gupta, Deepak, editor.
Goswami, Rajat Subhra, editor.
Banerjee, Subhasish, editor.
Tanveer, M., editor.
Pachori, Ram Bilas, 1979- editor.
Series
Lecture notes in electrical engineering ; v. 888.
Available in Other Form
PATTERN RECOGNITION AND DATA ANALYSIS WITH APPLICATIONS.
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Chapter 1. Revolutions in Infant fingerprint Recognition-A Survey
Chapter 2. A Review of High Utility Itemset Mining for Transactional Database
Chapter 3. A Cross-sectional study on distributed mutual exclusion algorithms for ad hoc networks
Chapter 4. Electromagnetic Pollution Index Estimation of Green Mobile Communication of Macrocell
Chapter 5. Prediction of Train delay System in Indian Railways using Machine Learning Techniques: Survey
Chapter 6. Valence of emotion recognition using EEG
Chapter 7. A Deep Learning-based Approach for Automated Brain Tumor Segmentation in MR images
Chapter 8. MZI based Electro-Optic Reversible XNOR/XOR Derived from Modified Fredkin Gate
Chapter 9. Secured Remote Access of Cloud Based Learning Management System (LMS) Using VPN
Chapter 10. Surface EMG signal classification for hand gesture recognition
Chapter 11. Improved Energy Efficiency in Street Lighting: A Coverage based Approach
Chapter 12. Security and Challenges for Cognitive IOT Based Future City Architecture
Chapter 13. A Heuristic Model for Friend Selection in Social Internet of Things
Chapter 14. A Fuzzy string matching based reduplication with morphological attributes
Chapter 15. Accelerating LOF Outlier Detection Approach. etc.

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