Machine learning algorithms and applications / / edited by Mettu Srinivas, G. Sucharitha and Anjanna Matta

• Pubblicazione: Hoboken, New Jersey : , : John Wiley & Sons, , [2021]; ©2021
• Descrizione fisica: 1 online resource (305 pages)
• Disciplina: 006.31
• Soggetto topico: Machine learning; Computer algorithms; Deep learning (Machine learning)
• Persona (resp. second.): SucharithaG; SrinivasMettu; MattaAnjanna
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 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 -- 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 -- 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 -- Index -- End User License Agreement.
• Titolo autorizzato: Machine learning algorithms and applications
• ISBN: 1-119-76925-6; 1-119-76926-4; 1-119-76924-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910811112903321
• Lo trovi qui: Univ. Federico II