Details

Subject(s)

• Artificial intelligence [Browse]
• Computational intelligence [Browse]

Editor

• Abraham, Ajith, 1968- [Browse]

Series

• Advances in Intelligent Systems and Computing [More in this series]
• Advances in Intelligent Systems and Computing ; v.1375 [More in this series]

Bibliographic references

Includes bibliographical references and index.

Source of description

Description based on print version record.

Contents

• Intro
• Preface
• HIS-NaBIC 2020 Organization
• General Chairs
• Program Chairs
• Publication Chairs
• Publicity Chairs
• International Program Committee
• Contents
• Vertical Interior Distance Ratio to Minimum Bounding Rectangle of a Shape
• 1 Introduction
• 2 Related Work
• 2.1 CCD (Centroid Contour Distance)
• 2.2 SC (Shape Context)
• 3 VIDR
• 3.1 Minimum Bounding Rectangle
• 3.2 Vertical Interior Distance Proportional Distribution
• 3.3 Shape Matching
• 4 Experimental Results and Analysis
• 5 Conclusion
• References
• Auto-Encoder Based Wavelet and Extreme Learning Machine for Face Recognition
• 2 Proposed Approach
• 2.1 Deep Learning
• 2.2 Wavelet Neural Network (WNN)
• 2.3 Extreme Learning Machine
• 2.4 Auto-Encoder
• 2.5 ELM Auto-Encoder
• 2.6 The Proposed Model
• 3 Results
• 3.1 Database Description
• 3.2 Results and Discussion
• 4 Conclusion
• Sparse Wavelet Auto-encoder for Covid-19 Cases Identification
• 2 Stacked Sparse Auto-encoders
• 3 Methodology
• 4 Sparse Auto-encoder Based Patches
• 5 Deep Network Based on Stacked Auto-encoders
• 6 Experimental Results and Discussion
• 7 Conclusion
• Design Guide Prediction Model for the Legal Interactions (GPM-LI)
• 2 Build GPM-LI
• 2.1 Preprocessing Stage
• 2.2 Build GPM-LI Predictor
• 3 Experiments
• Unsupervised Image Segmentation Using THMRF Model
• 2 Tweedie Hidden Markov Random Field Models: THMRF Models
• 3 Parameters Estimation: The THMRF-EMM Algorithm
• 3.1 The Proposed Segmentation Algorithm
• 3.2 Evaluation Criteria
• 3.3 The Proposed Segmentation Algorithm with Synthetic Image (K=2 Regions)
• 3.4 The Proposed Segmentation Algorithm with Real Brain MRI
• References.
• Maximizing an Organization's Operating Enactment in the Areas of Planning and Management
• 2 Material and Method
• 2.1 Research Objective and Scope
• 2.2 Research Problem
• 2.3 Methodology
• 2.4 Design/Scheme of Research
• 3.1 Data Collection Planning and Organizational Management
• 3.2 Data Analysis
• 4 Discussions
• 5 Conclusions
• Accent and Gender Recognition from English Language Speech and Audio Using Signal Processing and Deep Learning
• 2 Relevant Literature
• 3 Speech Classification Modeling
• 3.1 Problem Statement
• 3.2 English Language Accent Dataset
• 3.3 Feature Extraction Algorithms
• 3.4 Deep Learning Architecture Search
• 3.5 Experimental Setup
• 4 Results and Discussion
• Improved Path Planning with Memory Efficient A* Algorithm and Optimization of Narrow Passages
• 2 Related Work on Path Finding Algorithms
• 3 Distance Calculation and Grid Navigation
• 4 Considered Algorithms
• 5 Computational Experiments
• 5.1 Model
• 5.2 Simulations
• 5.3 Simulation Settings
• 6 Results
• 7 Conclusions
• Intelligent Mobile Application to Determine the Existence of Medicines Associated with COVID-19 in a Social Network of Medical Dispensaries in a Smart City
• 2 Dataset Analysis
• 3 Selection of Adequate Metaheuristics to Optimize the Problem: Cultural Algorithms
• 4 Intelligent Tool Developed
• 5 Conclusions and Future Research
• NoSQL Data Lake: A Big Data Source from Social Media
• 2 Data Lake Concept
• 3 Related Work
• 4 Big Data Source
• 4.1 Social Media Data Extraction
• 4.2 Social Media Data Integration to NoSQL Data Lake
• 5 Implementation and Evaluation
• 6 Conclusion
• Text Classification Using Convolution Neural Networks with FastText Embedding
• 3 Proposed Methodology
• 3.1 Embedding Model Generation
• 3.2 Text to Feature Representation Module
• 3.3 Text Classification Training Module
• 3.4 Testing Module
• 4 Experiments
• 4.1 Text Corpus
• 5 Results and Analysis
• 5.1 Comparison with the Previous Techniques
• Deep Convolutional Neural Network Based on Wavelet Transform for Super Image Resolution
• 2 Related Works
• 3 Proposed Method
• 3.1 LR-Image Decomposition Based on DWT
• 3.2 The Convolutional Neural Network for Feature Extraction
• 3.3 HR-Image Reconstruction
• 4 Experimental Results
• Optimizing Instance Selection Strategies in Interactive Machine Learning: An Application to Fraud Detection
• 2 Interactive Learning
• 3 An Interactive Learning System for Fraud Detection
• 4 Instance Selection Strategies vs. Learning Curve
• 5 Validation and Results
• 6 Conclusions
• Building IoT Analytics and Machine Learning with Open Source Software for Prediction of Environmental Data
• 2 System Model Architecture with Applications
• 2.1 A Typical BigData Architecture
• 2.2 The Proposed System Model
• 2.3 Implementation Results
• 3 Conclusions
• ANFIS-Based Inverse Kinematics and Forward Dynamics of 3 DOF Serial Manipulator
• 2 Modeling and Analysis
• 2.1 Kinematic Analysis
• 2.2 Dynamic Analysis
• 3 Adaptive Neuro-Fuzzy Inference System
• 4.1 Inverse Kinematics
• 4.2 Forward Dynamics
• Design and Development of Intelligent Pesticide Spraying System for Agricultural Robot
• 2 Literature Review.
• 3 Design, Development and Testing
• 3.1 Tracked Mobile Manipulator
• 3.2 Spraying System Description
• 3.3 Circuit Design and Simulation
• 3.4 Fuzzy Logic Controller
• 4 Hardware Description and Experimentation
• Solving Dynamic Bag-of-Tasks Scheduling Problem in Heterogeneous Multi-cloud Environment Using Hybrid Bi-Level Optimization Model
• 2 DBoTSP Formulation
• 3 Proposed HBDBoTSP
• 3.1 Upper Level Optimization Procedure
• 3.2 Lower Level Optimization Procedure
• 4 Experimental Study
• Caching Mechanisms Evolution in CCN Architectures
• 2 CCN: Most Popular ICN Approach
• 3 Overview of Existing Caching Mechanisms
• 3.1 Performance Measures
• 3.2 Caching Mechanisms in CCN
• 3.3 Caching Mechanisms in Hybrid Solutions Combining SDN and CCN
• 4 Simulation Experiments
• 5 Issues and Future Research Directions
• 5.1 Caching Improvements with Users' Behaviour Support
• 5.2 Popular Content Caching
• 5.3 Large-Scale Caching Related Issues
• 5.4 Service Vs Data Caching
• 5.5 The Tradeoff Between Gain and Cost
• 5.6 Energy Efficiency
• 5.7 Security
• SentiLSTM: A Deep Learning Approach for Sentiment Analysis of Restaurant Reviews
• 3 Corpora Development
• 4 Methodology
• 4.1 Text to Vector Representation
• 4.2 Model Architecture
• 4.3 Sentiment Classifier Model
• 5 Experiments
• 5.1 Hyperparameters
• 5.2 Results
• Characterizing Antennas' Radiation Pattern Using Bernoulli Lemniscates
• 2 Linkage System and Lemniscates of Bernoulli
• 3 Linkage System for Lemniscate Curves
• 4 Applications and Insights
• 4.1 Applications to Some Common Antennas
• 4.2 Discussion and Insights
• A Appendices.
• A.1 Proof of Proposition 1
• A.2 Proof of Proposition 2
• A.3 Proof of Proposition 3
• Analysis of Metaheuristics Feature Selection Algorithm for Classification
• 2 Research Methodology
• 2.1 Data Set Description
• 3 Result and Discussion
• 3.1 Comparison of CHPSO-DE and Filter-Based Feature Selection Technique
• 3.2 Comparison of CHPSO-DE and Wrapper-Based Metaheuristics Feature Selection Technique
• 3.3 Evaluation of the Performance of Feature Selection Algorithm Using Education Datasets
• Hybrid Genetic Algorithms to Solve the Traveling Salesman Problem
• 3 The Traveling Salesman Problem
• 4 Hybrid Solution Approach
• 4.1 Nearest Neighbor Algorithm
• 4.2 Adapted Genetic Algorithm
• 5 Computation Experiments and Results
• 5.1 Experiment Setup
• 6 Discussion
• 7 Conclusion and Outlook
• Hybridization of Adaboost with Random Forest for Real-Time Prediction of Online Shoppers' Purchasing Intention
• 2 Literature Review
• 3 Suggested System
• 3.1 Functional Description
• 3.2 Data Description
• 3.3 Prediction
• 4 Experiments and Results
• 5 Conclusion and Prospects
• Change Detection in Satellite Imagery: A Multi-label Approach Using Convolutional Neural Network
• 3.1 Preparation of Dataset
• 3.2 Application of Sliding Window on Satellite Images
• 3.3 Data Augmentation
• 3.4 Preprocessing and Post-processing of Images
• 3.5 Neural Network Architecture
• 3.6 Loss and Activation Function
• 5 Conclusion and Future Work
• Inverse Neural Control of a Magnetic Levitation System: Experimental Results
• 2 System Analysis
• 2.1 System Modeling.
• 2.2 System Parameters.

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ISBN

3-030-73050-6

OCLC

1247085648

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