Omnipresence of Intelligent Systems in Modern Society

Preface

PART I: VISUAL COMPUTING

1. Machine Learning/Deep Learning in Biometric Systems

Introduction

Machine Learning Methodology in Biometric Systems

Discussion About Methodologies

Conclusion & Future of Biometrics systems

References

2. Rolling Mean-based Real-time Activity Detection and Alert Generation using Deep Learning

Introduction

Literature Review

Proposed Methodology

Simulation and Results

Conclusion

References

PART II: SMART SYSTEMS AND IOT

3. A Triple Based Lightweight Authentication Scheme for Smart Grid and Smart Metering System

Introduction

Motivation

Proofing Copy Proofing Copy

Literature Survey

Existing Authentication Schemes

Problem Overview

Proposed Methodology

Error Calculation

Result and Discussion

Conclusion and Future Scope

References

4. A Comparative Analysis of Cloud-Based Education and Skill Development in Smart Cities Context

Introduction

Literature Review

Proposed Study

Analysis

Conclusion

References

5. Private Blockchain Based Encryption Framework using Computational Intelligence Approaches

Introduction

Blockchain Systems: Core Components

Computational Intelligence Approaches

Blockchain Encryption Mechanisms

Integrating Computational Intelligence (CI) with Blockchain Encryption

Challenges and Potential Solutions

Blockchain-Powered AI Innovations

Real-World Challenges in Implementing CI-Enhanced Blockchains

Future Directions

Conclusions and Future Scope

References

6. Leveraging AI in Smart Healthcare for Future Hospitals: Potential Applications and Challenges

Introduction

Technical Progress in Medical Sectors

Different AI Models in Healthcare

Potential Areas of AI Implementation

Discussion on Explainable AI

Discussion

Conclusion

References

PART III: COMPUTATIONAL ALGORITHMS

7. Discrete Artificial Bee Colony Optimization Algorithm for Cyber-attack Detection to Mitigate Credential Stuffing in Cyber Defense

Introduction

Literature Survey

Problem Definition

Proposed Discrete Artificial Bee Colony Algorithm

Experimental Analysis

Conclusion

References

8. Qryptographix: Quantum Image Encryption via Random Gates

Introduction

Related Work

Implementation

Feasibility of Implementation on Current and Near-Future Quantum Hardware

Result and Discussion

Conclusion

References

PART IV: AI AND HEALTHCARE

9. Handling Missing Data in Healthcare with Fuzzy Clustering Imputation

Introduction

Missing Data in Healthcare

Overview of Data Imputation Techniques

Fuzzy Clustering for Data Imputation

Experimental Setup

Results

Applications in Healthcare Datasets

Challenges in Implementing Fuzzy Clustering for Large Datasets

Conclusion

References

10. A Novel Weighted Ensemble Approach for Improved Brain Tumor Detection and Classification

Introduction

Literature Review

Proposed Model

Results and Discussions

Conclusion & Future Scope

Acknowledgments

References

11. Glioma Brain Tumour Grade Detection using Clinical Feature, Molecular Feature and ConvLSTM Network

Introduction

Techniques Used

Proposed Method

Result

Discussion

Conclusion

References

12. Machine Learning for Ocular Disease Detection in Fundus Images

Introduction

Related Works

Methodology

Results and Discussions

Conclusion

References

Index

Biography

Gautam Kumar is associated with the Department of Computer Science and Engineering as an Assistant Professor at the National Institute of Technology Delhi, India. His research includes image processing and computer vision, machine learning and deep learning, Robotics and healthcare applications.

Aditya Gupta is an Assistant Professor at Thapar Institute of Engineering and Technology in Patiala, India. Aditya has contributed significantly to his field, having published numerous papers in esteemed journals and successfully concluded centrally funded research projects. His research focuses on machine learning, edge computing, and health informatics.

Gunjan is an Assistant Professor at the National Institute of Technology Delhi, India. Her research interests include energy techniques in wireless sensor networks, machine learning, and health informatics.

Jayeeta Chakraborty is an Assistant Professor in the School of Computer Science, Kalinga Institute of Industrial Technology, Bhubaneswar. Her current research interests include human gait analysis, pattern recognition, signal and image processing as well as data mining, recommendation systems, and semantic web.