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Computational intelligence for multi...
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Sangaiah, Arun Kumar, (1981-)

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  • Computational intelligence for multimedia big data on the cloud with engineering applications /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Computational intelligence for multimedia big data on the cloud with engineering applications // edited by Arun Kumar Sangaiah, Michael Sheng, Zhiyong Zhang.
    其他作者: Sangaiah, Arun Kumar,
    面頁冊數: 1 online resource :illustrations.
    內容註: Front Cover; Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications; Copyright; Contents; Contributors; Foreword; Preface; Organization of the Book; Audience; 1 A Cloud-Based Big Data System to Support Visually Impaired People; 1.1 Introduction; 1.2 Related Work; 1.3 Background; 1.3.1 Internet of Things (IoT); 1.3.2 Cloud Computing; 1.3.3 Face Detection and Recognition; 1.3.4 Optical Character Recognition (OCR); 1.4 Problem Statement; 1.5 System Architecture; 1.5.1 Top-Level Architecture; 1.6 Big Data Analytics; 1.6.1 Text Recognition
    內容註: 1.6.2 Face Recognition1.7 Prototype; 1.8 Evaluation; 1.9 Conclusion; References; 2 Computational Intelligence in Smart Grid Environment; 2.1 Introduction; 2.1.1 Power Load Forecasting; 2.1.2 Electricity Price Forecasting; 2.1.3 Smart Grid Optimization; 2.2 Related Work and Open Issues; 2.2.1 Power Load Forecasting; 2.2.1.1 Stream Forecasting; 2.2.1.2 Adaptivity; 2.2.2 Prediction of Electricity Spot Prices in Smart Grid; 2.2.3 Optimization and Metaheuristics in Big Data and Microgrids; 2.3 Overview of Methods Used in Smart Grid Problems; 2.3.1 Forecasting Methods
    內容註: 2.3.1.1 Statistical Techniques2.3.1.2 Arti cial Intelligence Techniques; 2.3.1.3 Hybrid Techniques (Ensemble Learning); 2.3.2 Optimization Methods; 2.3.2.1 Particle Swarm Optimization; 2.3.2.2 Arti cial Bee Colony; 2.3.2.3 Genetic Algorithm; 2.3.2.4 Hyper-Heuristics; 2.4 Proposed Methods; 2.4.1 Electricity Price Forecasting; 2.4.2 Power Load Forecasting; 2.4.2.1 Adaptive Ensemble Learning for Power Load Forecasting; 2.4.2.2 Online Support Vector Regression; 2.4.2.3 Data; 2.4.2.4 Results; 2.5 Future Work; 2.6 Conclusions; Acknowledgment; References
    內容註: 3 Patient Facial Emotion Recognition and Sentiment Analysis Using Secure Cloud With Hardware Acceleration3.1 Introduction; 3.2 System Overview; 3.3 Background; 3.3.1 Facial Emotion Recognition; 3.3.2 Big Data Analytics on the Cloud; 3.3.3 Deep Learning Using Convolutional Neural Networks (CNNs); 3.4 System Architecture; 3.4.1 Face Detection in Images; 3.4.2 Facial Emotion Recognition Using CNNs; 3.4.3 The CNN Model Training; 3.5 System Implementation; 3.5.1 A Secure, Multi-tenant Cloud Storage System; 3.6 Experiments; 3.6.1 Dataset; 3.6.2 GPU Benchmarking and Comparison
    內容註: 3.6.3 Facial Emotion Recognition Accuracy3.6.4 Model Performance and Power With Hardware Acceleration; 3.7 DeepPain: Mapping Patient Emotions to Pain Intensity Levels; 3.8 Conclusions and Future Work; Acknowledgments; References; 4 Novel Computational Intelligence Techniques for Automatic Pain Detection and Pain Intensity Level Estimation From Facial Expressions Using Distributed Computing for Big Data; 4.1 Introduction; 4.2 Background and History of Computational Techniques; 4.2.1 Feature Extraction Techniques; 4.2.2 Dimension Reduction Techniques
    標題: Computational intelligence. -
    電子資源: https://www.sciencedirect.com/science/book/9780128133149
    ISBN: 9780128133279
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