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[null,"1.","Record Nr.",null,"UNINA9910845600403321"]
[null,null,"Autore",null,"Swarnkar Suman Kumar"]
[null,null,"Titolo",null,"Supervised and Unsupervised Data Engineering for Multimedia Data"]
[null,null,"Pubbl/distr/stampa",null,"Newark : , : John Wiley & Sons, Incorporated, , 2024"]
[{"$nulls":4},"©2024"]
[null,null,"ISBN",null,"1-119-78644-4"]
[{"$nulls":4},"1-119-78643-6"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (332 pages)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Cover -- Title Page -- Copyright Page -- Dedication Page -- Book Description -- Contents -- List of Figures -- List of Tables -- Preface -- Chapter 1 SLRRT: Sign Language Recognition in Real Time -- 1.1 Introduction -- 1.2 Literature Survey -- 1.3 Model for Sign Recognition Language -- 1.4 Experimentation -- 1.5 Methodology -- 1.6 Experimentation Results -- 1.7 Conclusion -- Future Scope -- References -- Chapter 2 Unsupervised/Supervised Feature Extraction and Feature Selection for Multimedia Data: (Feature extraction with feature selection for Image Forgery Detection) -- 2.1 Introduction -- 2.2 Problem Definition -- 2.3 Proposed Methodology -- 2.4 Experimentation and Results -- 2.5 Feature Selection &amp -- Pre-Trained CNN Models Description -- 2.6 Bat ELM Optimization Results -- Conclusion -- Declarations -- Consent for Publicaton -- Conflict of Interest -- Acknowledgement -- References -- Chapter 3 Multimedia Data in Healthcare System -- 3.1 Introduction -- 3.2 Recent Trends in Multimedia Marketing -- 3.3 Challenges in Multimedia -- 3.4 Opportunities in Multimedia -- 3.5 Data Visualization in Healthcare -- 3.6 Machine Learning and its Types -- 3.7 Health Monitoring and Management System Using Machine Learning Techniques -- 3.8 Health Monitoring Using K-Prototype Clustering Methods -- 3.9 AI-Based Robotics in E-Healthcare Applications Based on Multimedia Data -- 3.10 Future of AI in Health Care -- 3.11 Emerging Trends in Multimedia Systems -- 3.12 Discussion -- References -- Chapter 4 Automotive Vehicle Data Security Service in IoT Using ACO Algorithm -- Introduction -- Literature Survey -- System Design -- Result and "]
[{"$nulls":4},"Discussion -- Conclusion -- References -- Chapter 5 Unsupervised/Supervised Algorithms for Multimedia Data in Smart Agriculture -- 5.1 Introduction -- 5.2 Background."]
[{"$nulls":4},"5.3 Applications of Machine Learning Algorithms in Agriculture -- References -- Chapter 6 Secure Medical Image Transmission Using 2-D Tent Cascade Logistic Map -- 6.1 Introduction -- 6.2 Medical Image Encryption Using 2D Tent and Logistic Chaotic Function -- 6.3 Simulation Results and Discussion -- 6.4 Conclusion -- Acknowledgement -- References -- Chapter 7 Personalized Multi-User-Based Movie and Video Recommender System: A Deep Learning Perspective -- 7.1 Introduction -- 7.2 Literature Survey on Video and Movie Recommender Systems -- 7.3 Feature-Based Solutions for Movie and Video Recommender Systems -- 7.4 Fusing: EF - (Early Fusion) and LF - (Late Fusion) -- 7.5 Experimental Setup -- 7.6 Conclusions -- References -- Chapter 8 Sensory Perception of Haptic Rendering in Surgical Simulation -- Introduction -- Methodology -- Background Related Work -- Application -- Case Study -- Future Scope -- Result -- Conclusion -- Acknowledgement -- References -- Chapter 9 Multimedia Data in Modern Education -- Introduction to Multimedia -- Traditional Learning Approaches -- Applications of Multimedia in Education -- Conclusion -- References -- Chapter 10 Assessment of Adjusted and Normalized Mutual Information Variants for Band Selection in Hyperspectral Imagery -- Introduction -- Test Datasets -- Methodology -- Statistical Accuracy Investigations -- Results and Discussion -- Conclusion -- References -- Chapter 11 A Python-Based Machine Learning Classification Approach for Healthcare Applications -- Introduction -- Methodology -- Discussion -- References -- Chapter 12 Supervised and Unsupervised Learning Techniques for Biometric Systems -- Introduction -- Various Biometric Techniques -- Major Biometric-Based Problems from a Security Perspective -- Supervised Learning Methods for Biometric System -- Unsupervised Learning Methods for Biometric System -- Conclusion."]
[{"$nulls":4},"References -- About the Editors -- Index -- EULA."]