Applications of Computational Intelligence: Third IEEE Colombian Conference, ColCACI 2020, Cali, Colombia, August 7-8, 2020, Revised Selected Papers ... in Computer and Information Science, 1346) [1st ed. 2021] 3030697738, 9783030697730

This book constitutes revised and extended selected papers of the Third IEEE Colombian Conference, ColCACI 2020, held in

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Applications of Computational Intelligence: Third IEEE Colombian Conference, ColCACI 2020, Cali, Colombia, August 7-8, 2020, Revised Selected Papers ... in Computer and Information Science, 1346) [1st ed. 2021]
 3030697738, 9783030697730

Table of contents :
Preface
Organizers
Contents
Earth Sciences Applications
Understanding the Cotopaxi Volcano Activity with Clustering-Based Approaches
1 Introduction
2 Materials and Methods
2.1 Volcano Seismic Event Dataset
2.2 Clustering-Based Classifiers
2.3 Experimental Setup
3 Results and Discussion
3.1 Performance of Explored Models
3.2 State of Art-Based Comparison
4 Conclusions and Future Work
References
Seismic Event Classification Using Spectrograms and Deep Neural Nets
1 Introduction
2 Materials and Methods
2.1 Spectrogram Images Dataset
2.2 Deep-Learning Networks
2.3 Proposed Method
2.4 Experimental Setup
3 Results and Discussion
3.1 Performance Evaluation of the Proposed Method
3.2 State of the Art Based Comparison
4 Conclusions and Future Work
References
An Android App to Classify Culicoides Pusillus and Obsoletus Species
1 Introduction
2 Materials and Methods
2.1 Automatic Culicoides Species Classification
2.2 Development Environment
2.3 Proposed MosCla App
2.4 Experimental Setup
3 Results and Discussion
3.1 Classification Performance
3.2 MosCla App Feasibility
4 Conclusions and Future Work
References
Hammerhead Shark Species Monitoring with Deep Learning
1 Introduction
2 Materials and Methods
2.1 YOLOv3 Framework
2.2 Mask-RCNN Framework
2.3 Proposed Method
2.4 Shark Database
2.5 Experimental Setup
3 Results and Discussion
3.1 Performance of Proposed Method
3.2 Deep-Learning Models Comparison
4 Conclusions and Future Work
References
Towards Automatic Comparison of Online Campaign Versus Electoral Manifestos
1 Introduction
2 Materials and Methods
2.1 Architecture
2.2 Case Study
3 Results and Discussion
4 Conclusions and Future Work
References
Biomedical and Power Applications
Time and Frequency Domain Features Extraction Comparison for Motor Imagery Detection
1 Introduction
2 Methodology
2.1 Database
2.2 Feature Extraction
2.3 Machine Learning Techniques
3 Results
4 Discussion
5 Conclusions
References
Automatic Classification of Diagnosis-Related Groups Using ANN and XGBoost Models
1 Introduction
2 Related Works
2.1 Diagnosis-Related Groups - DRG
2.2 Traditional Method of DRG Classification
2.3 Classification of Patients in DRG Using ML
3 Methods
4 Dataset
4.1 Cohort of Study
5 Experiments and Results
5.1 Experimental Setup
5.2 Results
6 Conclusions
References
Power Management Strategies for Hybrid Vehicles: A Comparative Study
1 Introduction
2 Vehicle Longitudinal Dynamic
2.1 Engine Model
2.2 Electric Motor Model
2.3 Battery Model
3 Power Management Strategy
3.1 PMS Rule-Based
3.2 PMS Based Fuzzy
4 Simulation Results
5 Conclusion
References
Alternative Proposals and Its Applications
FCM Algorithm: Analysis of the Membership Function Influence and Its Consequences for Fuzzy Clustering
1 Introduction
2 Clustering and Fuzzy Clustering
3 Fuzzy C-Means Method
3.1 Fuzzy C-Means Algorithm
3.2 Analysis of FCM Algorithm
4 Proposal
5 Experiments and Results
5.1 Dataset and Parameter Setting
5.2 Experimental Results and Discussions
6 Conclusions
References
Echo State Network Performance Analysis Using Non-random Topologies
1 Introduction
2 Literature Review
3 Echo State Network Model
4 Experiments and Results
4.1 Problem Statement
4.2 Dataset Preparation
4.3 Implementation Setup
4.4 Methodology
5 Results
6 Conclusion
References
Deep Learning-Based Object Classification for Spectral Images
1 Introduction
2 Method
2.1 Data Acquisition
2.2 Pre-processing of the Data
2.3 CNN Architecture
3 Results
3.1 Simulation with 29 Spectral Bands
3.2 Dimensinality Reduction
3.3 Simulation Applying Different Levels of Gaussian Noise
4 Conclusions
References
Transfer Learning for Spectral Image Reconstruction from RGB Images
1 Introduction
2 RGB Acquisition
3 Transfer Learning Strategy
4 Simulations and Results
4.1 Datasets
4.2 Models
4.3 Metrics and Configurations
4.4 Results
5 Conclusions
References
Author Index

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