This book covers the 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 involve 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 modeling 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, multitask,
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).
General
Imprint: |
Springer Verlag, Singapore
|
Country of origin: |
Singapore |
Series: |
Lecture Notes in Electrical Engineering, 858 |
Release date: |
June 2023 |
First published: |
2022 |
Editors: |
Deepak Gupta
• Koj Sambyo
• Mukesh Prasad
• Sonali Agarwal
|
Dimensions: |
235 x 155mm (L x W) |
Pages: |
876 |
Edition: |
1st ed. 2022 |
ISBN-13: |
978-981-19-0842-2 |
Categories: |
Books
|
LSN: |
981-19-0842-7 |
Barcode: |
9789811908422 |
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