Computational Intelligence and Data Analytics (eBook, PDF)
Proceedings of ICCIDA 2024
Redaktion: Frery, Alejandro C.; Sarma, T. Hitendra; Kovvur, Ram Mohan Rao; Buyya, Rajkumar
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Computational Intelligence and Data Analytics (eBook, PDF)
Proceedings of ICCIDA 2024
Redaktion: Frery, Alejandro C.; Sarma, T. Hitendra; Kovvur, Ram Mohan Rao; Buyya, Rajkumar
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This book presents high-quality research papers presented at the International Conference on Computational Intelligence and Data Analytics (ICCIDA 2024), organized by the Department of Information Technology, Vasavi College of Engineering, Hyderabad, India, in June 2024. ICCIDA provides an excellent platform for exchanging knowledge with the global community of scientists, engineers, and educators. This book covers cutting-edge research in two prominent areas-computational intelligence and data analytics and allied research areas.
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This book presents high-quality research papers presented at the International Conference on Computational Intelligence and Data Analytics (ICCIDA 2024), organized by the Department of Information Technology, Vasavi College of Engineering, Hyderabad, India, in June 2024. ICCIDA provides an excellent platform for exchanging knowledge with the global community of scientists, engineers, and educators. This book covers cutting-edge research in two prominent areas-computational intelligence and data analytics and allied research areas.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Springer Nature Singapore
- Seitenzahl: 438
- Erscheinungstermin: 1. April 2025
- Englisch
- ISBN-13: 9789819604517
- Artikelnr.: 73759374
- Verlag: Springer Nature Singapore
- Seitenzahl: 438
- Erscheinungstermin: 1. April 2025
- Englisch
- ISBN-13: 9789819604517
- Artikelnr.: 73759374
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Alejandro C. Frery received his Ph.D. in Applied Computing from the Instituto Nacional de Pesquisas Espaciais (INPE, São José dos Campos, Brazil, 1993) and his Postdoctoral from IMPA. In 2003, he became Full Professor at the Universidade Federal de Alagoas, Brazil. He was University Vice-Chancellor for Research, Graduate Courses, and Innovation from Jan'2016 to Jan'2020. Currently, he is Statistics and Data Science Professor, at Victoria University of Wellington, New Zealand. Prof. Frery was Editor-in-Chief of the IEEE Geoscience and Remote Sensing Letters (2014-18). He was Distinguished Lecturer for IEEE GRSS (2015-19). In 2018, he received the IEEE GRSS Regional Leader Award. Prof. Frery served in various capacities in IEEE GRSS (Advisory Committee) AdCom, in the past 2 decades. Since 2023, he has been Vice-President of Publications. Dr. Rajkumar Buyya is Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia. He has authored over 750 publications and seven textbooks. He is the World's Top-Cited(#1) Author and the World's Most Productive(#1) Author in Cloud Computing. He served as Founding Editor-in-Chief of the IEEE Transactions on Cloud Computing. Dr. Buyya has been recognized as Web of Science's "Highly Cited Researcher" for four consecutive years since 2016, IEEE Fellow, Scopus Researcher of the Year 2017 with Excellence in Innovative Research Award by Elsevier, and the "Best of the World", in Computing Systems field, by The Australian 2019 Research Review. Dr. Ram Mohan Rao Kovvur received Ph.D. in Computer Science and Engineering from JNTUH in the year 2014 with a Research specialization in Grid Computing. He has over 27 years of teaching experience and served in various administrative capacities. Currently, he is Professor and Head of the Information Technology Department, at Vasavi College of Engineering, Hyderabad, INDIA. He has published 35 technical papers in reputed Journals and Conferences. He is Principal Investigator of the project titled "Drone/UAV Based Multi-Sensor High-Quality Precision Photogrammetry Laser Mapping and Data Capture, Processing for Geo-Spatial Platforms" funded by DST, India (34.78 lakh). Dr. Rao has established a Deep Learning Lab under the MODROBS Scheme of AICTE-INDIA with a grant of ¿19.31 Lakhs. Dr. T. Hitendra Sarma received Ph.D. in Computer Science and Engineering from JNT University Anantapur, India, in December 2013. He has more than 15 years of teaching and research experience. Currently, he is working as Associate Professor in the Department of Information Technology, at Vasavi College of Engineering, Hyderabad, India. Dr. Sarma has published more than 36 research articles in various peer-reviewed International Journals and Conferences published by Springer, Elsevier, and IEEE. Dr. Sarma completed a project titled "Dimensionality Reduction and Pixel Classification in Hyperspectral Images", funded by the Science and Engineering Research Board (SERB), India (2019-2021). He served as Volume Editor for the proceedings of ICECIT2015 & ICECIT2018 (Springer-LNEE), ICCIDA2022 (Springer-LNDECT), and MIGARS-2023 (IEEE). Dr. Sarma is Senior Member of IEEE, IEEE CIS, IEEE GRSS, ACM, IE(I), and CSI.
On-demand Cold Start Frequency Reduction with Off-Policy Reinforcement Learning in Serverless Computing.- Benchmarking Covariance Matrix Evolution Strategies on Autonomous Parking Navigation.- Easy accuracy improvement of fuzzy modelling using available datasets.- An Efficient Approach to Forest Fire Segmentation in Satellite Images using Superpixels based Fuzzy Clustering and CIELch Color Model.- An Improved XGBoost Classifier for MicroExpression Recognition using Hybrid Optimization Algorithm.- Detecting Equity Bubbles and Financial Crashes with Machine Learning.
On-demand Cold Start Frequency Reduction with Off-Policy Reinforcement Learning in Serverless Computing.- Benchmarking Covariance Matrix Evolution Strategies on Autonomous Parking Navigation.- Easy accuracy improvement of fuzzy modelling using available datasets.- An Efficient Approach to Forest Fire Segmentation in Satellite Images using Superpixels based Fuzzy Clustering and CIELch Color Model.- An Improved XGBoost Classifier for MicroExpression Recognition using Hybrid Optimization Algorithm.- Detecting Equity Bubbles and Financial Crashes with Machine Learning.