Next-Generation Networks and Deployable Artificial Intelligence
Springer International Publishing (Verlag)
978-3-032-15394-4 (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 an assistant professor in the Department of Computer Science & Engineering of Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India. Previously, he has worked in the Department of Computer Science & Engineering of National Institute of Technology Arunachal Pradesh. He received a Ph.D. degree in Computer Science & 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 an associate editor of the Journal of Neural Networks, Computers and Electrical Engineering, etc.
Dr. Dushyant Kumar Singh is an associate professor in the Department of Computer Science and Engineering at MNNIT Allahabad. He has more than 15 years of teaching and research experience. His areas of research interest are computer vision, image processing, embedded design, IoT, and high-performance computing. He is working toward developing intelligent solutions for vision-based problems. In his career, he has published more than 80 research papers in reputed journals and conference proceedings. He had delivered a good number of invited talks at many reputed institutions. He is a member of ACM and a senior member of IEEE. He has received a good number of grants from DST SERB for executing research projects, conducting high-end workshops, etc. He also served many of the administrative duties in the parent institute and outside too.
Dr. Divya Kumar is an associate professor in the Department of Computer Science and Engineering at Motilal Nehru National Institute of Technology (MNNIT), Allahabad, India. He earned his Ph.D. from the same institution, focusing on innovative computational techniques. His primary research interests include software engineering, soft computing, evolutionary optimization, blockchain technology, machine learning, and deep learning. Over the years, he has contributed significantly to these areas, with numerous publications in reputed international journals and conferences.
Dr. Girija Chetty has a Bachelors and Masters degree in Electrical Engineering and Computer Science from India and Ph.D. in Information Sciences and Engineering from Australia. She has more than 38 years of experience in Industry, Research and Teaching from Universities and Research and Development Organisations from India and Australia and has held several leadership positions including head of Software Engineering and Computer Science, program director of ITS courses, and course director for Master of Computing and Information Technology Courses. Currently, she is a full professor in Computing and Information Technology at School of Information Technology and Systems, at University of Canberra, Australia, and leads a research group with several Ph.D. students, Post-Docs, research assistants and regular international and national visiting researchers.
Optimized Feature Selection Using Proposed Enhanced Firefly Algorithm.- Harnessing Neural Networks for Outlier Detection: A Comparative Review.- Vector-Borne Disease Prediction.- Integrating Artificial Intelligence in Medical Imaging: Enhancing Diagnostic Accuracy through Multi-Stream Attention-Based CNNs, Addressing Multi-Modal Data Challenges, and Improving Clinical Outcomes.- Parkinson s Disease Classification from Biomedical Voice Measurement: A Multi-Algorithm Approach.- Wide Activation Super Resolution Generative Adversarial Network with Orthogonal Regularization.- Cross-Dataset Dermatology Framework: HAM10000 Training with ISIC Testing.- Conversational Companion Orchestrator Based on AI with Image Recognition and Generation.- Detecting Indian Sign Language Using YOLO.- PDRaDeX: Parkinson s Disease Classification using Radiomics Features with Explainable AI and MRI Data.
| Erscheint lt. Verlag | 23.3.2026 |
|---|---|
| Reihe/Serie | Lecture Notes in Networks and Systems |
| Zusatzinfo | Approx. 700 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 • Next-generation networks (NGN) • Proceedings of NGNDAI 2025 |
| ISBN-10 | 3-032-15394-8 / 3032153948 |
| ISBN-13 | 978-3-032-15394-4 / 9783032153944 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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