Intro
Preface
Contents
About the Editors
Impact of Data Centric Approach to Improve the Performance of Leaf Disease Classification
1 Introduction
2 Literature Survey
3 Experiment Setup
4 Conclusion
References
Evolution, Trends, and Future Developments of Business Intelligence
1 Introduction
2 Literature Review
2.1 Business Intelligence as of Today
2.2 History of Business Intelligence
2.3 Future of Business Intelligence
3 Methodology
4 Research Gap
5 Problem Statement
6 Objectives

7 Identifying the Techniques Used in Business Intelligence
7.1 Analytics
7.2 Predictive Modeling
7.3 Data Mining
7.4 OLAP (Online Analytical Proceedings)
7.5 Modeling Visualization
8 Discussion on Evolution, Trends, and Future Developments of Business Intelligence
9 Conclusion
References
A Secure Protocol for Authentication and Data Storage for Healthcare System
1 Introduction
2 Proposed Work
3 Security Analysis of Proposed Protocol
3.1 Scyther-Automated Security Protocol Verification Tool
4 Conclusion
References

OMA-DSS: Ontology Based Multi Agent Decision Support System in Healthcare Domain to Prevent Cardiovascular Diseases
1 Introduction
2 Multi Agent Systems and Ontology
3 Proposed MAS System
3.1 Detailed View of OMA-DSS
4 Conclusion and Future Scope
References
Innovative Task Scheduling and Allocation Algorithm for E-Governance with Multi-cloud Environment
1 Introduction
2 Literature Survey
3 Proposed Methodology
3.1 Cloud Scheduling Algorithm
3.2 Cloud Allocation Algorithm
4 Result and Discussion
5 Conclusion
References

Distributed Deep Learning with Data Parallelism for Diabetic Retinopathy Classification
1 Introduction
2 Literature Survey
2.1 Deep Learning
2.2 DDL
2.3 DR Classification
3 Methodology
3.1 Dataset
3.2 DL Model
3.3 Data Parallelism in DDL
3.4 Experimental Setup
4 Results and Discussions
5 Conclusions
6 Future Scope
References
STING-A User Governed Crime Alert App
1 Introduction
2 Related Works
3 Proposed Methodology
4 Experimental Analysis and Results
5 Conclusion
References

Classification of Traffic Signal Images Using Deep Neural Networks
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 DataSet
3.2 Implementation
3.3 Performance Metrics of Our Model
3.4 Methodology
4 Results and Discussion
5 Conclusion
References
Automatic Evaluation for Machine Translation
1 Introduction
2 Literature Review
3 Methodology
3.1 Bilingual Evaluation Understudy (BLEU)
3.2 Metric for Evaluation of Translation with Explicit Ordering (METEOR)
3.3 Translation Error Rate (TER)