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Data Science and Network Engineering = proceedings ICDSNE 2024 /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Data Science and Network Engineering/ edited by Suyel Namasudra ... [et al.].
Reminder of title:
proceedings ICDSNE 2024 /
other author:
Namasudra, Suyel.
corporate name:
Workshop on the Preservation of Stability under Discretization
Published:
Singapore :Springer Nature Singapore : : 2025.,
Description:
xvii, 398 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:
Springer Nature eBook
Subject:
Telecommunication - Congresses. -
Online resource:
https://doi.org/10.1007/978-981-97-8336-6
ISBN:
9789819783366
Data Science and Network Engineering = proceedings ICDSNE 2024 /
Data Science and Network Engineering
proceedings ICDSNE 2024 /[electronic resource] :edited by Suyel Namasudra ... [et al.]. - Singapore :Springer Nature Singapore :2025. - xvii, 398 p. :ill. (some col.), digital ;24 cm. - Lecture notes in networks and systems,v. 11652367-3389 ;. - Lecture notes in networks and systems ;v.1..
Hyperparameter Tuning of Fine-Tuned VGG19 Using Sine Cosine Algorithm for Acute Lymphoblastic Leukemia Detection -- Computer Vision and Deep Learning-based Model for Detecting Spoofed Faces in Images -- Explainable AI Insights into a Time Series Weather Prediction Model Using Stacked LSTM -- Patient-specific and Patient-independent Seizure Prediction using Ensemble Learning Technique -- An Intuitive and Modular Framework for Enhanced Human-Machine Synergy -- Wavelet-Transformed k-NN Pipeline for EEG-Based Eye Blink Classification with Time Wrapping.
This book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2024) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 12-13, 2024. It includes research works from researchers, academicians, business executives, and industry professionals for solving real-life problems by using the advancements and applications of data science and network engineering. This book covers many advanced topics, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering.
ISBN: 9789819783366
Standard No.: 10.1007/978-981-97-8336-6doiSubjects--Topical Terms:
675653
Telecommunication
--Congresses.
LC Class. No.: TK5101.A1 / I58 2024
Dewey Class. No.: 621.382
Data Science and Network Engineering = proceedings ICDSNE 2024 /
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Hyperparameter Tuning of Fine-Tuned VGG19 Using Sine Cosine Algorithm for Acute Lymphoblastic Leukemia Detection -- Computer Vision and Deep Learning-based Model for Detecting Spoofed Faces in Images -- Explainable AI Insights into a Time Series Weather Prediction Model Using Stacked LSTM -- Patient-specific and Patient-independent Seizure Prediction using Ensemble Learning Technique -- An Intuitive and Modular Framework for Enhanced Human-Machine Synergy -- Wavelet-Transformed k-NN Pipeline for EEG-Based Eye Blink Classification with Time Wrapping.
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This book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2024) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 12-13, 2024. It includes research works from researchers, academicians, business executives, and industry professionals for solving real-life problems by using the advancements and applications of data science and network engineering. This book covers many advanced topics, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering.
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