Details

Subject(s)

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

Editor

• de la Iglesia, Daniel H. [Browse]
• Paz Santana, Juan F. de [Browse]
• López Rivero, Alfonso J. [Browse]

Series

Advances in intelligent systems and computing ; Volume 1430. [More in this series]

Bibliographic references

Includes bibliographical references and index.

Source of description

Description based on print version record.

Contents

• Intro
• Preface
• Organization
• Program Committee
• Scientific Committee
• Organizing Committee
• DITTET 2021 Organizers
• DITTET 2021 Collaborates
• Contents
• Track on Artificial Intelligence
• Deep Learning Based Approaches for Vehicle Make and Model Recognition
• 1 Introduction
• 2 Related Work
• 3 Proposed Methodology
• 4 Deep Learning Approaches
• 4.1 Convolutional Neural Network
• 4.2 ResNeXt-50
• 4.3 Support Vector Machine with VGG-16
• 5 Experimental Setup
• 6 Results and Discussions
• 7 Conclusion
• References
• Comparing Machine Learning vs. Humans for Dietary Assessment
• 3 Experimental Setup
• 3.1 Bag-of-Words Architecture
• 3.2 Deep Learning Architecture(s)
• 3.3 Baseline Survey
• 4 Comparison Study
• 4.1 Additional Results, CNN (16 Classes) vs. HVS
• 4.2 More (20) Epochs Impact on CNN Accuracy
• 4.3 Human, Resnet, Inception and Bag-of-Words
• 5 Conclusions
• Drawing Music: Using Neural Networks to Compose Descriptive Music from Illustrations
• 2.1 Feature Extraction from Multimedia Files
• 2.2 Relationship Between Multimedia Features
• 2.3 Musical Composition
• 3 Composing Music Based on User's Drawings
• 3.1 Extracting Image Features
• 3.2 Obtaining Chords from an Audio File
• 3.3 Relating Visual and Musical Descriptors
• 3.4 Composing Music
• 4 Results and Discussion
• 4.1 Performance of the Classifiers
• 4.2 Quality of the Musical Composition
• 4.3 Interconnection Between Image and Music
• A Method to Identify Graphs Containing a Specific Sub-graph
• 3 Proposed Method
• 4 Experiment
• 4.1 With Room Light Only
• 4.2 With Sunlight
• 4.3 With Shadows Caused by Light
• 5 Conclusion
• References.
• An Advertising Real-Time Intelligent and Scalable Framework for Profiling Customers' Emotions
• 3 Proposed Framework
• 3.1 Architecture
• 3.2 Implementation
• 4 Experimental Work
• An Intelligent and Scalable IoT Monitoring Framework for Safety in Civil Construction Workspaces
• 2 Proposed Framework
• 3 Implementation
• 4 Results and Discussions
• Exploring Feature Extraction to Vulnerability Prediction Problem
• 2 Background
• 2.1 Vulnerability Prediction Models - VPM
• 2.2 The Cold Start Problem
• 2.3 Instance Violation Feature Extraction
• 2.4 Related Work
• 3 Empirically Evaluation
• 3.1 Experiment Design
• 3.2 Metrics
• 3.3 Experiments
• 3.4 Experimental Results
• 4 Conclusions
• A Spanish Political Tweets Fine-Tuned Sentiment Analysis Model
• 2.1 Natural Language Processing
• 2.2 Sentiment Analysis
• 3 Proposed System
• 3.1 Dataset Translation
• 3.2 Model Fine-Tuning
• 4 Case Study
• 4.1 Dataset
• 4.2 NLP Models
• 4.3 Metrics
• 5 Results
• 6 Conclusions
• European Union Fosters Ethical AI in the Public Administration
• 2 The EU Driving Force on Ethical AI in Public Administration
• 3 National Strategies for the Implementation of AI
• 4 Discrimination
• 5 Framing the Ethics of the Use of AI in the Public Sector
• 6 Explainability
• 7 Conclusions
• Auto-Tagger of Contextual Activity Tags for Music Tracks
• 2 Related Works
• 3 Materials and Methods
• 3.1 Multi-label Classification Approaches
• 3.2 Dataset
• 4 Results
• 5 Conclusions and Future Works
• Object Detection Through Computer Vision
• 2 The Methodology
• 3 Case Study.
• 5 The Conclusions and the Future Work
• Bias Analysis on Twitter
• 3 The Bias Analysis System
• 3.1 Model Parameters
• 3.2 Building of Training Corpus
• 3.3 Model Generation
• 4 Case Study and Results
• 5 Conclusions and Future Extensions
• Towards the Detection of Hateful Sentiment in Social Networks
• 1 Conceptual Foundations of the Automatic Processing of Discourse in Social Networks
• 2 Opinion Mining
• 3 Natural Language Processing
• 4 Feature Extraction
• 5 Evaluation Criteria
• 6 Methodology and Experimentation
• 7 Results
• 8 Conclusions and Further Work
• MusicFactory: Application of a Convolutional Neural Network for the Generation of Soundscapes from Images
• 2.1 Images Recognition
• 2.2 Soundscapes Generation
• 3.1 Image Recognition Module
• 3.2 Creating Soundscapes
• 3.3 User Interface
• 5 Conclusions and Future Work
• Track on Technological Ethics
• Papal Teaching on the Ethical Challenges of Artificial Intelligence
• 2 An Ethical Preliminary - Recognizing Bias
• 3 Which Ethical Framework Are We Using?
• 4 Conclusion
• The Role of the Right to Explanation and Its Safeguards in the Realization of Trustworthy AI
• 1 Introduction, Background, Scope, and Definition
• 2 Right to Explanation in the European Union
• 3 Safeguards Around Right to Explanation
• 3.1 The Right to Obtain Information About Automated Decisions
• 3.2 The Right to Contest/Challenge the Automated Decision
• 3.3 The Right to Express One's Point of View
• 3.4 The Right to Obtain Human Intervention
• 3.5 The Right to Obtain an Explanation of the Decision After Assessment.
• 4 Ethical Principles on Explainability and Right to Explanation
• 5 The Effect of Right to Explanation on Trustworthy AI
• 6 Conclusion
• A Tool to Help Learning Programming
• 2 Motivation
• 3 Tool for the Students
• Track on Disruptive Technologies
• A Cost-Effective Framework for Monitoring Disaster Recovery Infrastructures
• 5 Results and Discussion
• Validating an Evaluation Tool to Assess Older People's Acceptance Towards a Humanoid Robot Companion: A University of the Third Age Pilot Study
• 2 Elder Users' Acceptance of Social Robots and Evaluation Tools
• 3 Validation of the Acceptance Evaluation Tool
• 3.1 Participants
• 3.2 Materials and Procedure
• 3.3 Results
• 4 Discussion
• Semantic Web and Others as Disruptive Technologies at the Service of University Transparency. A Use Case
• 1.1 Use of CRIS Systems at University
• 1.2 Use of CERIF Ontology
• 1.3 CRIS and Institutional Repositories at University
• 2 Methodology
• 2.1 Data Models
• 3 Results
• 3.1 Data retrieval and Integration System
• 3.2 Data Visualization, Querying and Downloading System
• CoCoBot, A Low Cost Humanoid Robot Companion for Elderly People
• 2 Architecture
• 2.1 Physical Layer
• 2.2 Reactive Layer
• 2.3 Deliberative Layer
• 2.4 Control Layer
• 3 Conclusion
• Influence of Air Temperature and Relative Humidity on the Electrical Behaviour of Smart Textiles
• 2 Electrical Behaviour of Materials
• 3 Electrical Measurement of Lamellar Textiles
• 4 Results and Discussion
• 5 Conclusions and Future Work
• Population-Based Methods to Reduce the Colors of an Image
• 2 Ant-Based Solutions
• 3 PSO-Based Solutions
• 4 ABC-Based Solutions
• 5 Firefly-Based Solutions
• 6 Frogs-Based Solutions
• 7 Mixed Methods
• 8 Comparison of Results
• Use of YOLOv4 and Yolov4Tiny for Intelligent Vehicle Detection in Smart City Environments
• 2.1 Deep Learning Techniques
• 2.2 Datasets in the Context of Vehicle Detection
• 3 Materials and Proposed Model
• 4.1 Metrics
• 4.2 Evaluation Method
• 4.3 Model Evaluation Results
• Track on Doctoral Consortium
• Multi-Agent System Design-Based Smart Device for Aquatic-Accidents Alerting and Avoidance
• 2.1 Machine Vision Systems
• 2.2 Sensor Systems
• 3.1 Sensorization System
• 3.2 Multi-Agent System
• 4 Results and Conclusions
• A Scalable Smart Lighting Framework to Save Energy
• 3 Architecture
• 5 Discussion
• 6 Conclusions and Future Work
• A Scalable Framework to Predict Bitcoin Price Using Support Vector Machine
• 3 Framework
• 5 Results and Analysis
• CDonVR: E-learning of a Cash Dispenser on Virtual Reality
• 5 Conclusions and Future Works
• Competencies: An Exploratory Analysis of Performance Evaluations Results
• 4 Developing Experiments and Analyzing Results
• 5 Conclusion and Future Works
• Application of Educational Support Through Disruptive Technology in Deaf Student Learning.
• 1 Introduction and Background.

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ISBN

3-031-14859-2

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