Details

Subject(s)

• Artificial intelligence [Browse]
• Computational intelligence [Browse]
• Signal processing [Browse]

Editor

• Bhattacharyya, Siddhartha, 1975- [Browse]

Series

• Advances in Intelligent Systems and Computing [More in this series]
• Advances in Intelligent Systems and Computing ; v.1312 [More in this series]

Bibliographic references

Includes bibliographical references and index.

Source of description

Description based on print version record.

Contents

• Intro
• Preface
• Acknowledgements
• Contents
• About the Editors
• Performance Analysis of Machine Learning Algorithms Over a Network Traffic
• 1 Introduction
• 2 Literature Survey
• 3 Problem Specifications
• 4 Implementation
• 4.1 The Dataset
• 4.2 The Supervised Learning
• 4.3 The Multilayer Perceptron (MLP)
• 4.4 The Random Forest Classifier
• 4.5 The Support Vector Machine (SVM)
• 5 The Performance Evaluation and Results
• 5.1 The Accuracy
• 6 Conclusion and Future Work
• References
• Binary PSO-Based Feature Selection and Neural Network for Parkinson's Disease Prediction
• 2 Methodology
• 2.1 Neural Networks
• 3 Results and Discussions
• 4 Conclusion
• An Evolutionary-Based Additive Tree for Enhanced Disease Prediction
• 2 Related Work
• 3 Methodology
• 4 Results and Discussions
• 5 Conclusion
• Novel Defense Framework for Cross-layer Attacks in Cognitive Radio Networks
• 1.1 AI for Cognitive Radio Networks
• 2 Related Works
• 3 Attack Models
• 3.1 PHY Layer Attack Model
• 3.2 Defense Scheme
• 3.3 MAC Layer Attack Model
• 3.4 Defense Scheme
• 3.5 Cross-Layer Attack
• 3.6 Cross-Layer Defense
• 4 Results
• 4.1 Simulation Setup
• 4.2 Results
• Texture Based Image Retrieval Using GLCM and LBP
• 2 Theoretical Background
• 2.1 Gray Level Co-occurrence Matrixes (GLCM)
• 2.2 Local Binary Patterns (LBP)
• 3 Experimental Results
• 3.1 Statistical Analysis
• Reference
• Design and Development of Bayesian Optimization Algorithms for Big Data Classification Based on MapReduce Framework
• 2 Correlative Naive Bayes Classifier (CNB)
• 3 Cuckoo Grey Wolf Optimization with Correlative Naïve Bayes Classifier (CGCNB).
• 4 Fuzzy Correlative Naive Bayes Classifier (FCNB)
• 5 Holoentropy Using Correlative Naïve Bayes Classifier for a Big Data Classification (HCNB)
• 6 Results and Discussion
• 6.1 Performance Evaluation
• 7 Conclusion
• An IoT-Based BLYNK Server Application for Infant Monitoring Alert System to Detect Crying and Wetness of a Baby
• 3 The Proposed Architecture of Baby Monitoring System
• 3.1 Baby Cry Detection Algorithm
• 3.2 Wetness Detection Algorithm
• 4 Experimental Results
• 4.1 Noise Detection by the System
• 4.2 Playing Songs
• 4.3 Wetness Detection
• 4.4 Turning on the Fan
• 5 Conclusions and Future Work
• Analysis of DEAP Dataset for Emotion Recognition
• 2.1 Foundations
• 3 Procedure
• 5 Conclusions and Discussions
• A Machine Learning Approach for Air Pollution Analysis
• 4 Analysis of Linearity and Correlation Between Gases Using Machine Learning
• 5 Conclusions
• Facial Expression Detection Model of Seven Expression Types Using Hybrid Feature Selection and Deep CNN
• 1.1 Edge Detection and CNN
• 3 Proposed Model
• 3.1 About the Model
• 3.2 Data Flow of the Model
• 3.3 Proposed Algorithm and Model
• 3.4 FaceImgRecog Advanced
• 4 Experiment and Results
• 4.1 Dataset and Execution
• 4.2 Graphical Representation of Results
• 4.3 Comparison Table
• 5 Conclusion and Future Work
• A Fuzzy Approach for Handling Relationship Between Security and Usability Requirements
• 2 Relationship Between Usability and Security
• 2.1 Usability
• 2.2 Security
• 3 Fuzzy Approach to Develop Usable-Secure System
• 4 Implementation and Results
• References.
• Naive Bayes Approach for Retrieval of Video Object Using Trajectories
• 2 Motivations
• 2.1 Literature Review
• 2.2 Research Gaps
• 3 Proposed Method
• 3.1 Object Tracking Based on Hybrid NSA-NARX Model
• 3.2 Retrieval of Objects Using the Naive Bayes Classifier
• 4 Results and Discussion
• 4.1 Performance Metrics
• 4.2 Comparative Analysis
• Mobility-Aware Clustering Routing (MACRON) Algorithm for Lifetime Improvement of Extensive Dynamic Wireless Sensor Network
• 1 Related Work
• 1.1 Need of Scheduling in Wireless Sensor Network
• 2 Proposed Work
• 2.1 Proposed Algorithm
• 3 Results
• An Extensive Survey on IOT Protocols and Applications
• 3 Block Diagram of IOT
• 4 Applications of IOT
• 5 IOT Protocols at Different Layers
• 6 Conclusion
• Review on Cardiac Arrhythmia Through Segmentation Approaches in Deep Learning
• 2 Survey Over Various Heart Sound Detection Techniques
• 2.1 Heart Sound Detection Using Empirical Mode Decomposition
• 2.2 Heart Sound Detection Through Tunable Quality Wavelet Transform (TQWT)
• 2.3 Heart Sound Detection Using Feature Extraction
• 3 Comparative Analysis of Various Segmentation Approaches Used in HS Detection
• 3.1 Heart Sound Detection Based on S-Transform
• 3.2 Classification Techniques for Heart Sound Detection
• 4 Heart Sound Detection Using Deep Learning Approaches
• Fast Medicinal Leaf Retrieval Using CapsNet
• 2 Proposed Approach
• 2.1 Pre-processing
• 2.2 CapsNet Design and Training Process
• 3 Experimental Setup and Results
• 3.1 Evaluation Parameters
• Risk Analysis in Movie Recommendation System Based on Collaborative Filtering.
• 1 Recommendation System
• 1.1 Types of Recommendation System
• 2 Implementation
• 2.1 Single Objective Using Java
• 2.2 Multiobjective Using Python
• 3 Conclusion
• Difficult on Addressing Security: A Security Requirement Framework
• 1 Introduction of the Security
• 2 The Need of Software Security and Existing Research Approach
• 3 Framework for Software Security in Requirement Phase
• 4 The Proposed Security Requirement Framework (SRF)
• 5 The FrameWork
• 6 Validation of the Framework
• Smart Eye Testing
• 2 Literature Review
• 3 Implementation
• Ameliorated Shape Matrix Representation for Efficient Classification of Targets in ISAR Imagery
• 2 Ameliorated Shape Matrix Representation
• 2.1 Finding the Axis-of-Reference
• 2.2 Finding Rmax and Rmin
• 2.3 Shape Matrix Generation
• 2.4 Classification
• Region-Specific Opinion Mining from Tweets in a Mixed Political Scenario
• 3 Proposed Methodology
• 3.1 Data Collection
• 3.2 Wrangling
• 3.3 Preprocessing
• 3.4 Sentiment Analysis
• Denoising of Multispectral Images: An Adaptive Approach
• Digital Watermarking to Protect Deep Learning Model
• 3 Convolution Neural Network Model
• 3.1 Image Pre-processing and Data Generation
• 3.2 Training the Fully Connected Neural Network
• 4 Proposed Methodology
• 4.1 Watermarking the Neural Network
• 4.2 Implementation
• 5 Results and Discussion
• Sequential Nonlinear Programming Optimization for Circular Polarization in Jute Substrate-Based Monopole Antenna
• 2 Proposed Antenna Design and Parametric Analysis
• 3 Optimization Using SNLP Optimizer
• 3.1 Optimizing the Variable S, UL, and UW
• Genetic Algorithm-Based Optimization in the Improvement of Wideband Characteristics of MIMO Antenna
• 2 Antenna Designing
• 3 Genetic Algorithm Optimizer Analysis
• 3.1 Optimizing the Parameter BP1, BP2, and LP1
• Design and Analysis of Optimized Dimensional MIMO Antenna Using Quasi-Newton Algorithm
• 3 Quasi-Newton Optimizer Analysis
• 3.1 Optimizing the Parameter of RL and Rw
• Preserving the Forest Natural Resources by Machine Learning Intelligence
• 2 Discussion on Existing Algorithms
• 2.1 Polyphonic Detection Systems
• 2.2 Classification Techniques
• 2.3 Mel-Frequency Cepstral Coefficients (MFCC)
• 2.4 K-Nearest Neighbour Method
• 2.5 Deep Neural Networks (DNN)
• 3 Analysis on Sound Event in Forest Environment
• Comprehensive Study on Different Types of Software Agents
• 2 Related Work and Discussion
• 2.1 Collaborative Agents
• 2.2 Interface Agents
• 2.3 Mobile Agent
• 2.4 Information/Internet Agents
• 2.5 Reactive Agents
• 2.6 Hybrid Agents
• 2.7 Smart Agents
• 3 Implementation of Software Agent
• 3.1 Overview
• 3.2 Algorithm
• 4 Result
• Hybrid Acknowledgment Scheme for Early Malicious Node Detection in Wireless Sensor Networks
• 3 Proposed System
• 4 Algorithm
• 5 Increased Network Lifetime
• 6 Enhanced Throughput
• Prediction of Temperature and Humidity Using IoT and Machine Learning Algorithm.

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ISBN

981-336-176-X

OCLC

1243550943

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