Machine Learning Algorithms and Applications

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Srinivas, Mettu
Otros Autores: Sucharitha, G., Matta, Anjanna
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated, 2021.
Temas:
Computer algorithms.
Deep learning.
Machine learning.
Algorithmes.
Apprentissage automatique.
algorithms.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Table of Contents
  • Title Page
  • Copyright
  • Acknowledgments
  • Preface
  • Part 1: Machine Learning for Industrial Applications
  • 1 A Learning-Based Visualization Application for Air Quality Evaluation During COVID-19 Pandemic in Open Data Centric Services
  • 1.1 Introduction
  • 1.2 Literature Survey
  • 1.3 Implementation Details
  • 1.4 Results and Discussions
  • 1.5 Conclusion
  • References
  • 2 Automatic Counting and Classification of Silkworm Eggs Using Deep Learning
  • 2.1 Introduction
  • 2.2 Conventional Silkworm Egg Detection Approaches
  • 2.3 Proposed Method
  • 2.4 Dataset Generation
  • 2.5 Results
  • 2.6 Conclusion
  • Acknowledgment
  • References
  • 3 A Wind Speed Prediction System Using Deep Neural Networks
  • 3.1 Introduction
  • 3.2 Methodology
  • 3.3 Results and Discussions
  • 3.4 Conclusion
  • References
  • 4 Res-SE-Net: Boosting Performance of ResNets by Enhancing Bridge Connections
  • 4.1 Introduction
  • 4.2 Related Work
  • 4.3 Preliminaries
  • 4.4 Proposed Model
  • 4.5 Experiments
  • 4.6 Results
  • 4.7 Conclusion
  • References
  • 5 Sakshi Aggarwal, Navjot Singh and K.K. Mishra
  • 5.1 Genesis
  • 5.2 The Big Picture: Artificial Neural Network
  • 5.3 Delineating the Cornerstones
  • 5.4 Deep Learning Architectures
  • 5.5 Why is CNN Preferred for Computer Vision Applications?
  • 5.6 Unravel Deep Learning in Medical Diagnostic Systems
  • 5.7 Challenges and Future Expectations
  • 5.8 Conclusion
  • References
  • 6 Two-Stage Credit Scoring Model Based on Evolutionary Feature Selection and Ensemble Neural Networks
  • 6.1 Introduction
  • 6.2 Literature Survey
  • 6.3 Proposed Model for Credit Scoring
  • 6.4 Results and Discussion
  • 6.5 Conclusion
  • References
  • 7 Enhanced Block-Based Feature Agglomeration Clustering for Video Summarization
  • 7.1 Introduction
  • 7.2 Related Works
  • 7.3 Feature Agglomeration Clustering
  • 7.4 Proposed Methodology
  • 7.5 Results and Analysis
  • 7.6 Conclusion
  • References
  • Part 2: Machine Learning for Healthcare Systems
  • 8 Cardiac Arrhythmia Detection and Classification From ECG Signals Using XGBoost Classifier
  • 8.1 Introduction
  • 8.2 Materials and Methods
  • 8.3 Results and Discussion
  • 8.4 Conclusion
  • References
  • 9 GSA-Based Approach for Gene Selection from Microarray Gene Expression Data
  • 9.1 Introduction
  • 9.2 Related Works
  • 9.3 An Overview of Gravitational Search Algorithm
  • 9.4 Proposed Model
  • 9.5 Simulation Results
  • 9.6 Conclusion
  • References
  • Part 3: Machine Learning for Security Systems
  • 10 On Fusion of NIR and VW Information for Cross-Spectral Iris Matching
  • 10.1 Introduction
  • 10.2 Preliminary Details
  • 10.3 Experiments and Results
  • 10.4 Conclusions
  • References
  • 11 Fake Social Media Profile Detection
  • 11.1 Introduction
  • 11.2 Related Work
  • 11.3 Methodology
  • 11.4 Experimental Results
  • 11.5 Conclusion and Future Work
  • Acknowledgment
  • References

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