UID:
almafu_9961286949302883
Umfang:
1 online resource (362 p.).
ISBN:
9781394175246
,
1394175248
,
9781394175253
,
1394175256
Serie:
Artificial Intelligence and Soft Computing for Industrial Transformation
Anmerkung:
Chapter 7 A Systematic Review for Medical Data Fusion Over Wireless Multimedia Sensor Networks
,
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Part I: Medical Applications -- Chapter 1 Predictive Models of Alzheimer's Disease Using Machine Learning Algorithms -- An Analysis -- 1.1 Introduction -- 1.2 Prediction of Diseases Using Machine Learning -- 1.3 Materials and Methods -- 1.4 Methods -- 1.5 ML Algorithm and Their Results -- 1.6 Support Vector Machine (SVM) -- 1.7 Logistic Regression -- 1.8 K Nearest Neighbor Algorithm (KNN) -- 1.9 Naive Bayes -- 1.10 Finding the Best Algorithm Using Experimenter Application -- 1.11 Conclusion -- 1.12 Future Scope -- References
,
Chapter 2 Bounding Box Region-Based Segmentation of COVID-19 X-Ray Images by Thresholding and Clustering -- 2.1 Introduction -- 2.2 Literature Review -- 2.3 Dataset Used -- 2.4 Proposed Method -- 2.4.1 Histogram Equalization -- 2.4.2 Threshold-Based Segmentation -- 2.4.3 K-Means Clustering -- 2.4.4 Fuzzy-K-Means Clustering -- 2.5 Experimental Analysis -- 2.5.1 Results of Histogram Equalization -- 2.5.2 Findings of Bounding Box Segmentation -- 2.5.3 Evaluation Metrics -- 2.6 Conclusion -- References
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Chapter 3 Steering Angle Prediction for Autonomous Vehicles Using Deep Learning Model with Optimized Hyperparameters -- 3.1 Introduction -- 3.2 Literature Review -- 3.3 Methodology -- 3.3.1 Architecture -- 3.3.2 Data -- 3.3.3 Data Pre-Processing -- 3.3.4 Hyperparameter Optimization -- 3.3.5 Neural Network -- 3.3.6 Training -- 3.4 Experiment and Results -- 3.4.1 Benchmark -- 3.5 Conclusion -- References -- Chapter 4 Review of Classification and Feature Selection Methods for Genome-Wide Association SNP for Breast Cancer -- 4.1 Introduction -- 4.2 Literature Analysis
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4.2.1 Review of Gene Selection Methods in SNP -- 4.2.2 Review of Classification Methods in SNP -- 4.2.3 Review of Deep Learning Classification Methods in SNP -- 4.3 Comparison Analysis -- 4.4 Issues of the Existing Works -- 4.5 Experimental Results -- 4.6 Conclusion and Future Work -- References -- Chapter 5 COVID-19 Data Analysis Using the Trend Check Data Analysis Approaches -- 5.1 Introduction -- 5.2 Literature Survey -- 5.3 COVID-19 Data Segregation Analysis Using the Trend Check Approaches -- 5.3.1 Trend Check Analysis Segregation 1 Algorithm
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5.3.2 Trend Check Analysis Segregation 2 Algorithm -- 5.4 Results and Discussion -- 5.5 Conclusion -- References -- Chapter 6 Analyzing Statewise COVID-19 Lockdowns Using Support Vector Regression -- 6.1 Introduction -- 6.2 Background -- 6.2.1 Comprehensive Survey -- Applications in Healthcare Industry -- 6.2.2 Comparison of Various Models for Forecasting -- 6.2.3 Context of the Work -- 6.3 Proposed Work -- 6.3.1 Conceptual Architecture -- 6.3.2 Procedure -- 6.4 Experimental Results -- 6.5 Discussion and Conclusion -- 6.5.1 Future Scope -- References
Weitere Ausg.:
Print version: Umamaheswari, K. Artificial Intelligence for Sustainable Applications Newark : John Wiley & Sons, Incorporated,c2023 ISBN 9781394174584
Sprache:
Englisch
DOI:
10.1002/9781394175253
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9781394175253
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9781394175253
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9781394175253
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