UID:
almahu_9949420164402882
Format:
XII, 576 p. 306 illus., 230 illus. in color.
,
online resource.
Edition:
1st ed. 2023.
ISBN:
9789811930157
Series Statement:
Lecture Notes on Data Engineering and Communications Technologies, 139
Content:
The book features original papers from International Conference on Computational Methods and Data Engineering (ICCMDE 2021), organized by School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India, during November 25-26, 2021. The book covers innovative and cutting-edge work of researchers, developers, and practitioners from academia and industry working in the area of advanced computing.
Note:
Chapter 1. A Graph Based Extractive Assamese Text Summarization -- Chapter 2. Internet of Things (IoT) for Secure Data and M2M Communications -- Chapter 3. Deveelopment of Walking Assistants for Visually Challenged Person -- Chapter 4. A PERFORMANCE STUDY OF PREDICTION MODELS FOR DIABETES PREDICTION USING MACHINE LEARNING -- Chapter 5. Orthopantomogram (OPG) Image Analysis using Bounding Box Algorithm -- Chapter 6. Design and Analysis of an Improved Artificial Neural Network Controller for the Energy Efficiency Enhancement of Wind Power Plant -- Chapter 7. Detection of Renal Calculi using Convolutional Neural Networks -- Chapter 8. Question Answering and Text Generation using BERT and GPT-2 Model -- Chapter 9. Improved Lenet Model for Flower Classification Using GPU Computing -- Chapter 10. Distributed computing over the Next Generation Mobile Communication Network (NGMCN) is an emerging technology -- Chapter 11. The ELF Tribe: Redefining Primary Education in a Post-COVID Era -- Chapter 12. An Extreme Machine Learning Mdel for Evaluating Landslide Hazard Zonation in Nilgiris District, Causative Factors and Risk Assessment using Earth Observation Techniques -- Chapter 13. Analysis of Cross-Site Scripting Vulnerabilities in Various Day-to-Day Web Applications -- Chapter 14. Detecting Cyberbullying with text classification using 1DCNN and Glove Embeddings -- Chapter 15. A Bayesian Network Based Software Requirement Complexity Prediction Model.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9789811930140
Additional Edition:
Printed edition: ISBN 9789811930164
Language:
English
DOI:
10.1007/978-981-19-3015-7
URL:
https://doi.org/10.1007/978-981-19-3015-7
URL:
Volltext
(URL des Erstveröffentlichers)
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