Intelligent Computing and Networking

Proceedings of IC-ICN 2024
2025
ISBN: 978-981-97-8630-5
Verlag: Springer Nature Singapore

Buch, Englisch, Band 1172, 290 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 519 g

Reihe: Lecture Notes in Networks and Systems

This book gathers high-quality peer-reviewed research papers presented at the International Conference on Intelligent Computing and Networking (IC-ICN 2024), organized by the Computer Department, Thakur College of Engineering and Technology, in Mumbai, Maharashtra, India, on February 23–24, 2024. The book includes innovative and novel papers in the areas of intelligent computing, artificial intelligence, machine learning, deep learning, fuzzy logic, natural language processing, human–machine interaction, big data mining, data science and mining, applications of intelligent systems in healthcare, finance, agriculture and manufacturing, high-performance computing, computer networking, sensor and wireless networks, Internet of Things (IoT), software-defined networks, cryptography, mobile computing, digital forensics, and blockchain technology.

Zielgruppe

Research

Autoren/Hrsg.

Ghinea, George

Khandare, Anand

Semwal, Vijay Bhaskar

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Chapter 1: Identification of potholes and speed bumps using SSD & YOLO.- Chapter 2: Webcam-Based Real-Time Indian Sign Language Recognition for Inclusive Communication.- Chapter 3: Performance Analysis of Medical Image Fusion Using Wavelet Technique.- Chapter 4: Correlation Analysis and Stock Market Prediction of Nifty and Nasdaq Indices Using Machine Learning Techniques.- Chapter 5: Integrated RFID-Verified Smart Manufacturing System for Bottle production using industry 4.0.- Chapter 6: Comparing Advanced Programming Languages Based on Machine Learning (ML).- Chapter 7: Optimal Cluster and Node Balancing Technique using K-Mean based on Q-Learning for Wireless Sensor Network.- Chapter 8: Optimizing Iot Task Offloading With Federated Deep Reinforcement Learning In Vehicle And Industrial Environments.- Chapter 9: Enhancing Video Action Recognition with Spatial-Temporal Convolutional Attention Networks.- Chapter 10: Spatial Federated Learning Based Blockchain Mechanism for Smart Contract Vulnerability Detection. etc.

Über Autor(innen)

Dr. Gheorghita (George) Ghinea is a professor in Mulsemedia Computing in the Department of Computer Science, at Brunel University. Dr. Ghinea's research activities lie at the confluence of computer science, media, and psychology. In particular, his work focuses on the area of perceptual multimedia quality and how one builds end-to-end communication systems incorporating user perceptual requirements. Dr. Ghinea has applied his expertise in areas such as eye-tracking, telemedicine, multi-modal interaction, and ubiquitous and mobile computing. He has over 350 publications in his research field and is situated in the Top 2% Cited Scientists in the World, according to the prestigious Stanford Ranking (2020).

Vijay Bhaskar Semwal has been working as an assistant professor (CSE) at NIT Bhopal since February 5, 2019. Before joining NIT Bhopal, he was working at NIT Rourkela. He has also worked with IIIT Dharwad as an assistant professor(CSE) for two years (2016–2018) and he has also worked as an assistant professor (CSE) at NIT Jamshedpur. He has earned his doctorate degree in robotics from IIIT Allahabad (2017) , M.Tech. in Information Technology from IIIT Allahabad (2010), and B.Tech. (IT) from the College of Engineering Roorkee (2008). His areas of research are bipedal robotics, gait analysis and synthesis, artificial intelligence, machine learning, and theoretical computer science. He has published more than 15 SCI research papers. He has received early career research award by DST-SERB under the government of India.

Dr. Anand Khandare is the Professor and Associate Dean ( Planning & Operations-Digital Resources), Thakur College of Engineering and Technology, Mumbai, with 18 years of teaching experience. He completed Ph.D. in Computer Science and Engineering in the domain of data clustering in machine learning from Sant Gadge Baba Amravati University. He has a total of 60+ publications in national and international conferences and journals. He has one copyright and two patents. He guided various research and funded projects. He conducted corporate training on AIML and programming languages for the industries. He organized various conferences. He worked as a volume editor in Springer International Conference on Intelligent Computing and Networking for the Years 2020-24. He is also a reviewer in various journals and conferences.