Computational Methods in Science and Technology
Proceedings of the 4th International Conference on Computational Methods in Science & Technology (ICCMST 2024), 2-3 May 2024, Mohali, India, Volume 2
Herausgeber: Kaur, Sukhpreet; Kumar, Manish; Kamboj, Sushil
Computational Methods in Science and Technology
Proceedings of the 4th International Conference on Computational Methods in Science & Technology (ICCMST 2024), 2-3 May 2024, Mohali, India, Volume 2
Herausgeber: Kaur, Sukhpreet; Kumar, Manish; Kamboj, Sushil
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This book contains the proceedings of the 4TH International Conference on Computational Methods in Science and Technology (ICCMST 2024).
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This book contains the proceedings of the 4TH International Conference on Computational Methods in Science and Technology (ICCMST 2024).
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 560
- Erscheinungstermin: 2. Oktober 2024
- Englisch
- Abmessung: 244mm x 170mm x 32mm
- Gewicht: 1116g
- ISBN-13: 9781032911601
- ISBN-10: 1032911603
- Artikelnr.: 71263514
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 560
- Erscheinungstermin: 2. Oktober 2024
- Englisch
- Abmessung: 244mm x 170mm x 32mm
- Gewicht: 1116g
- ISBN-13: 9781032911601
- ISBN-10: 1032911603
- Artikelnr.: 71263514
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Prof.(Dr.) Sukhpreet Kaur is working as a Professor in CSE department at Chandigarh Engineering College, Landran, Mohali. She has in total of 15 years of vast experience in teaching and research. She has done Ph. D in CSE from I K Gujral Punjab Technical University, Jalandhar and has done her Masters in Technology in CSE from GNDEC, Ludhiana. The various research areas in which she worked includes Image Processing, Artificial Intelligence and Computer Vision. Prof.(Dr.) Sushil Kamoj is a distinguished Professor and Head of the Computer Science and Engineering (CSE) Department, with over 20 years of experience in academia and research. Renowned for his expertise in Computer Networks, Dr. Kamboj has made significant contributions to the field through his innovative research, teaching excellence, and leadership. He is dedicated to fostering academic growth and developing cutting-edge solutions to complex technological problems. Prof.(Dr.) Manish Kumar is working as a Professor in the Department of Computer Science and Engineering at Chandigarh Engineering College, Chandigarh Group of College, Landran, Mohali. He has a career academician with about 20 years of experience in teaching, research, academic and administrative outreach activities. As far as academic qualification is concerned he did B.Tech., M.Tech. and Ph.D. degree in Computer Science and Engineering. He has primarily specialization research in the area of Wireless sensor network, data mining and machine learning. To his credit he has more than 40 publications in widely circulated journals of national and international repute. He has actively organized several national and international conferences. He has organized the various conference and proceedings editor of ICMST 2020, 2021 and 2022. Prof.(Dr.) Arvind Dagur is currently working as Professor and Program Chair in school of Computing Science and Engineering, Galgotias University, Greater Noida, India. He worked as Professor & Dy. Head, in Department of Computer Science and Engineering, KEC (KIET Group) Ghaziabad. He has more than 18 Years of experience in Teaching and research. He completed Ph.D. (Computer Engineering) from Jamia Millia Islamia, New Delhi, India (A Central University), M.Tech. (Computer Science and Engineering) from MNNIT, Allahabad, India and B.Tech. (CSE) from UPTU, Lucknow. He has published more than 30 research papers in reputed international Journals / Conferences. His research papers are indexed in SCI, SCOPUS, DBLP, and ESCI, etc. He also published 5 book chapters in Springer Book series such as LNCS, AICS Series, and LNICST. He has chaired many sessions in various conferences and been a reviewer of many conferences and journals.He is the conference chair and proceedings editor of ICABCS 2023 and ICAIIT 2023 Dr. Dhirendra Kumar Shukla is currently working as Associate Professor in School of Computer Science & Engineering Department, He has total experience of more than 11 years of teaching Computer science and Engineering Department and has been associated with Galgotias University since 2022. He has published 11 Journal research Paper area of Cloud computing.
1. Synergistic Approach to Enhancing Teaching-Learning Processes through
the Integration of ICT and Machine Learning 2. Detection of Brain Tumor
from MRI Images using EfficientNet: A Deep Learning Approach 3. Proposed
Framework for Hybrid Multilevel Optimized Machine Learning Classification
in Apple Leaf Disease Detection 4. Estimation of sediment load in Mahanadi
River, India using artificial neural network 5. Prediction of water
discharge in Mahanadi River basin, India using artificial neural networks
6. Online misinformation detection using deep learning on social media: A
survey and analysis
the Integration of ICT and Machine Learning 2. Detection of Brain Tumor
from MRI Images using EfficientNet: A Deep Learning Approach 3. Proposed
Framework for Hybrid Multilevel Optimized Machine Learning Classification
in Apple Leaf Disease Detection 4. Estimation of sediment load in Mahanadi
River, India using artificial neural network 5. Prediction of water
discharge in Mahanadi River basin, India using artificial neural networks
6. Online misinformation detection using deep learning on social media: A
survey and analysis
1. Synergistic Approach to Enhancing Teaching-Learning Processes through
the Integration of ICT and Machine Learning 2. Detection of Brain Tumor
from MRI Images using EfficientNet: A Deep Learning Approach 3. Proposed
Framework for Hybrid Multilevel Optimized Machine Learning Classification
in Apple Leaf Disease Detection 4. Estimation of sediment load in Mahanadi
River, India using artificial neural network 5. Prediction of water
discharge in Mahanadi River basin, India using artificial neural networks
6. Online misinformation detection using deep learning on social media: A
survey and analysis
the Integration of ICT and Machine Learning 2. Detection of Brain Tumor
from MRI Images using EfficientNet: A Deep Learning Approach 3. Proposed
Framework for Hybrid Multilevel Optimized Machine Learning Classification
in Apple Leaf Disease Detection 4. Estimation of sediment load in Mahanadi
River, India using artificial neural network 5. Prediction of water
discharge in Mahanadi River basin, India using artificial neural networks
6. Online misinformation detection using deep learning on social media: A
survey and analysis