Читать книгу Machine Learning Algorithms and Applications - Группа авторов - Страница 2
Table of Contents
Оглавление1 Cover
5 Preface
6 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
7 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
8 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 12 Extraction of the Features of Fingerprints Using Conventional Methods and Convolutional Neural Networks 12.1 Introduction 12.2 Related Work 12.3 Methods and Materials 12.4 Results 12.5 Conclusion Acknowledgements References 13 Facial Expression Recognition Using Fusion of Deep Learning and Multiple Features 13.1 Introduction 13.2 Related Work 13.3 Proposed Method 13.4 Experimental Results 13.5 Conclusion Acknowledgement References
9 Part 4: Machine Learning for Classification and Information Retrieval Systems 14 AnimNet: An Animal Classification Network using Deep Learning 14.1 Introduction 14.2 Related Work 14.3 Proposed Methodology 14.4 Results 14.5 Conclusion References 15 A Hybrid Approach for Feature Extraction From Reviews to Perform Sentiment Analysis 15.1 Introduction 15.2 Related Work 15.3 The Proposed System 15.4 Result Analysis 15.5 Conclusion References 16 Spark-Enhanced Deep Neural Network Framework for Medical Phrase Embedding 16.1 Introduction 16.2 Related Work 16.3 Proposed Approach 16.4 Experimental Setup 16.5 Results 16.6 Conclusion References 17 Image Anonymization Using Deep Convolutional Generative Adversarial Network 17.1 Introduction 17.2 Background Information 17.3 Image Anonymization to Prevent Model Inversion Attack 17.4 Results and Analysis 17.5 Conclusion References
10 Index
