Data Management, Analytics and Innovation
Proceedings of ICDMAI 2025, Volume 3
Series: Lecture Notes in Networks and Systems; 1368;
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Product details:
- Publisher Springer Nature Singapore
- Date of Publication 4 October 2025
- Number of Volumes 1 pieces, Book
- ISBN 9789819665334
- Binding Paperback
- No. of pages426 pages
- Size 235x155 mm
- Language English
- Illustrations XVI, 426 p. 148 illus., 126 illus. in color. Illustrations, black & white 692
Categories
Long description:
This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at 9th International Conference on Data Management, Analytics and Innovation (ICDMAI 2025), held during 17–19 January 2025 at St. Xavier’s College (Autonomous), Kolkata, India. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. The book is divided into three volumes.
MoreTable of Contents:
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Chapter 1: Comparative Analysis of Different Generative AI Models For Scholarly Articles on Blockchain Technology.- Chapter 2: A Hybrid Model for Retail Success : Integrating RFM, Recommendations, and Price Dynamics.- Chapter3 : Artificial Intelligence: A Catalyst for Change in the Indian Automobile Industry.- Chapter 4: A comparative review on GAN-based data augmentation techniques for plant-based pest detection.- Chapter 5: Ensemble Based Prediction Analytics Model for Photoluminescence Intensity Decay in Silicon Nanostructures.- Chapter 6: Application of Artificial Intelligence (AI) and Internet of Things (IoT) in Smart Agriculture – A Systematic Review.- Chapter 7: Image-Based Automated Attendance System Designing Leveraging Multi-task Convolutional Neural Network.- Chapter 8: Safe-Steer: A Real-time IoT-based System for Driver Profiling Using Deep Learning.- Chapter 9: Exploring AI Applications and Innovations in Supply Chain Management.- Chapter 10: Anti-Money Laundering via Graph Convolution Neural Network based Hybrids.-
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