Next-Generation Networks and Deployable Artificial Intelligence
Springer International Publishing (Verlag)
978-3-032-15400-2 (ISBN)
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This book is a collection of best selected research papers presented at International Conference on Next-Generation Networks and Deployable Artificial Intelligence (NGNDAI-2025) organized by Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India, during September 18 20, 2025. The book includes original research by researchers working in the field of artificial intelligence, machine learning, intelligent networks, robotics, and next-generation communication technologies.
Dr. Deepak Gupta is Assistant Professor in the Department of Computer Science and Engineering of Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India. Previously he has worked in the Department of Computer Science and Engineering of National Institute of Technology Arunachal Pradesh. He received a Ph.D. degree in computer science and engineering from the Jawaharlal Nehru University, New Delhi, India. His research interests include support vector machines, ELM, RVFL, KRR, biomedical applications, and other machine learning techniques. He has published over 80 referred journal and conference papers of international repute. His publications have more than 2382 citations with an h-index of 28 and i10-index of 63 (Google Scholar, 01/02/2025). Recently, he has listed in the world's top 2% of scientists in a study carried out by Stanford University, USA, 2023, 2024. He is Associate Editor of the Journal of Neural Networks, Computers and Electrical Engineering, etc.
Prof. Mayank Pandey stands out as Distinguished Academic and Highly Esteemed Professor at Motilal Nehru National Institute of Technology (MNNIT), Allahabad. Renowned for his profound expertise in computer science, he has made significant contributions to research, innovation, and education, inspiring generations of students and peers. He earned his bachelor's degree in computer science engineering from GB Pant Engineering College, Pauri, Garhwal, followed by an M.Tech. from the prestigious Indian Institute of Technology (IIT) Kharagpur, and a doctorate from MNNIT Allahabad. Throughout his illustrious career, Prof. Pandey has exemplified a relentless commitment to advancing knowledge and fostering excellence in teaching, research, and innovation. One of his most notable achievements is his groundbreaking research on video analytics-based crowd management during the Kumbh Mela 2019 in Prayagraj.
Dr. Aditya Nigam received his M.Tech. and Ph.D. degrees from the Indian Institute of Technology (IIT) Kanpur in 2009 and 2014, respectively. He is currently Associate Professor at IIT Mandi, in the School of Computing and Electrical Engineering (SCEE). He joined IIT Mandi in August 2014 as Teaching Fellow and has since been deeply involved in both research and teaching. With a strong passion for teaching and mentoring, Dr. Nigam has been actively involved in delivering courses on deep learning and its applications over the last six years. His teaching approach spans from foundational concepts to advanced techniques, equipping students and researchers with the necessary skills to tackle real-world AI challenges. His research interests lie at the intersection of deep learning, biometrics, medical image analysis, image processing, computer vision, and machine learning.
Prof. Ram Bilas Pachori received the B.E. degree with honors in electronics and communication engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India, in 2001, and the M.Tech. and Ph.D. degrees in electrical engineering from IIT Kanpur, India, in 2003 and 2008, respectively. His research interests include signal and image processing, biomedical signal processing, non-stationary signal processing, speech signal processing, brain-computer interface, artificial intelligence and internet of things in healthcare, and machine learning for signal processing. He was Associate Editor of IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021-2024). Currently, he is Associate Editor of Electronics Letters, IEEE Open Journal of Engineering in Medicine and Biology, Computers and Electrical Engineering, and Biomedical Signal Processing and Control. He is also serving as Deputy Editor-in-Chief of IETE Journal of Research, Handling Editor of Signal Processing, and Editor of IETE Technical Review journal. He is Fellow of IEEE, INAE, IET, AAIA, IETE, and IEI.
Machine Learning for Cyber Attack Detection: Insights into Model Performance and Optimization.- Integrating Deep Learning and Augmented Reality for Personalized Dental Implantology : The Development and Application of the GIST-3DR System for Enhanced Precision and Visualization in Dental Implant Procedures.- TrafficMan: Bridging Vehicle Detection, Tracking, and RL for Intelligent Traffic Management.- A Density-based Approach for Personalized Tourist Recommendations.- Cloud-based Mango Leaf Disease Identification and Classification using Deep Learning.- Intelligent System : An aid for Jaundice detection using Deep Learning.- A Combined Approach to Hand Gesture and Face Recognition for Enhanced User Authentication.- Similarity Aware Few Shot Learning for Knowledge Graph Completion.- Abusive Comment Detection in Transliterated Bengali Corpus Using ML and DL Techniques.- A real time predictive approach for Credit Card Fraud Detection.
| Erscheint lt. Verlag | 29.3.2026 |
|---|---|
| Reihe/Serie | Lecture Notes in Networks and Systems |
| Zusatzinfo | Approx. 800 p. 90 illus. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Nachrichtentechnik | |
| Schlagworte | AI-Driven Network Management • Artificial Intelligence (AI) • Deep learning • Internet of Things (IoT) • machine learning • Machine Learning in Networking • Machine Learning in Networking • Next-generation networks (NGN) • Proceedings of NGNDAI 2025 |
| ISBN-10 | 3-032-15400-6 / 3032154006 |
| ISBN-13 | 978-3-032-15400-2 / 9783032154002 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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