Innovations in Electrical and Electronics Engineering : Proceedings of ICEEE 2024, Volume 2 (Lecture Notes in Electrical Engineering) （2024）

Kalam, Akhtar (EDT)/ Mekhilef, Saad (EDT)/ Williamson, Sheldon S. (EDT)

Springer Nature（2025/01発売）

• 製本 Hardcover:ハードカバー版／ページ数 628 p.
• 言語 ENG
• 商品コード 9789819791118

Full Description

This book features selected high-quality papers presented at the 2024 International Conference on Electrical and Electronics Engineering (ICEEE 2024), Jointly organized by ADSRS Education and Research and Swinburne University of Technology, Melbourne, Australia during September 11-12, 2024, at Advanced Technologies Centre, Swinburne University of Technology, 427-451 Burwood Rd, Hawthorn VIC 3122. The book covers electrical engineering topics—power and energy including renewable energy, power electronics and applications, control, and automation and instrumentation and book two covers the areas of robotics, artificial intelligence and IoT, electronics devices, circuits and systems, wireless and optical communication, RF and microwaves, VLSI, signal processing, and others. The book brings both single- and multidisciplinary research on these topics to provide the most up-to-date information in one place. The book offers an asset for researchers from both academia and industries involved in advanced studies.

Contents

1. SPP CNN Spatial Pyramid Pooling for Optimizing Brain Tumor Classification.- 2. KAN PDEs A Novel Approach to Solving Partial Differential Equations Using Kolmogorov Arnold Networks Enhanced Accuracy and Efficiency.- 3. Dynamic Indian Sign Language Sentence Captioning System Using Machine Learning.- 4. The Rehab Reco A Therapy Recommender System for Dementia.- 5. Implementation of Machine learning and Ensemble learning models for the prediction of CKD and drugs side effect.- 6. Adverse Weather Object Detection using Customised YOLO models.- 7. Cryptographic Security and Decentralization A Blockchain based Approach to Healthcare Data Integrity.- 8. Predicting Brain Age Using Lightweight 3D CNN Architecture from T1 Weighted MRI Images.- 9. Performance analysis of a Deep Learning-based Object Detection Approach for Post disaster Buildings Damage Level Assessment using YOLO and Faster R CNN.- 10. LSTM based Predictive Leader Follower Control Scheme for Networked Drones.