Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 25th Iberoamerican Congress, CIARP 2021, Porto, Portugal, May ... Papers (Lecture Notes in Computer Science)

Preface
Organization
Contents
Medical Applications
Predicting the Use of Invasive Mechanical Ventilation in ICU COVID-19 Patients
	1 Introduction
	2 State of the Art
	3 Data Set
	4 Methods
		4.1 Data Preparation
		4.2 Data Pre-processing
		4.3 Modelling
	5 Results
	6 Conclusions
	References
A Coarse to Fine Corneal Ulcer Segmentation Approach Using U-net and DexiNed in Chain
	1 Introduction
	2 Related Works
	3 Materials and Methods
		3.1 Evaluated CNN Architectures
		3.2 Image Dataset
		3.3 Evaluation Metrics
	4 Proposed Method
	5 Results and Discussion
	6 Conclusion
	References
Replacing Data Augmentation with Rotation-Equivariant CNNs in Image-Based Classification of Oral Cancer
	1 Introduction
	2 Methodology
	3 Oral Dataset
	4 Experiments
	5 Results
	6 Conclusions and Future Work
	References
A Multitasking Learning Framework for Dermoscopic Image Analysis
	1 Introduction
	2 Network Architecture and Learning Details
		2.1 Learning Details
	3 Experimental Design and Results
		3.1 Dataset and Implementation Details
		3.2 Experiments and Analysis
	4 Conclusions
	References
An Evaluation of Segmentation Techniques for Covid-19 Identification in Chest X-Ray
	1 Introduction
	2 Proposed Method
	3 Experimental Setup
		3.1 Parameters
		3.2 Data Augmentation
		3.3 Evaluation Metrics
	4 Results and Discussion
		4.1 Segmentation Performance
		4.2 COVID-19 Identification Scores
		4.3 Models Interpretability with LIME
	5 Conclusion
	References
A Study on Annotation Efficient Learning Methods for Segmentation in Prostate Histopathological Images
	1 Introduction
	2 Related Work
		2.1 Segmentation
		2.2 Cancer Detection in WSIs
		2.3 Unsupervised Representation Learning
	3 Methodology
		3.1 U-Net
		3.2 Transfer Learning
		3.3 Self-supervised Learning
	4 Evaluation
		4.1 Dataset
		4.2 Segmentation Results
	5 Conclusion
	References
Natural Language Processing
Data-Augmented Emoji Approach to Sentiment Classification of Tweets
	1 Introduction and Background
		1.1 Bidirectional Encoder Representations from Transformers (BERT)
	2 Methodology
		2.1 Datasets
		2.2 Additional Pre-training
		2.3 Data Augmentation
		2.4 Emoji Extraction
		2.5 Model Architecture
		2.6 Training Protocol
	3 Results
		3.1 Evaluation Metrics
		3.2 Pre-training Results
		3.3 Data Augmentation Results
		3.4 Fine-Tuning Results
	4 Conclusions
	References
Detecting Hate Speech in Cross-Lingual and Multi-lingual Settings Using Language Agnostic Representations
	1 Introduction
	2 Related Works
	3 Proposal
	4 Experiments
		4.1 Dataset
		4.2 Models and Evaluation Metrics
	5 Results
		5.1 Mono-lingual
		5.2 Multi-lingual
		5.3 Cross-Lingual
	6 Conclusions
	References
Prediction of Perception of Security Using Social Media Content
	1 Introduction
	2 Materials and Methods
		2.1 Proposed Model
		2.2 Estimating Model Parameters
		2.3 Predicting Future Tweets
		2.4 Experimental Settings
	3 Results
	4 Conclusions
	References
Metaheuristics
Fine-Tuning Dropout Regularization in Energy-Based Deep Learning
	1 Introduction
	2 Related Works
	3 Theoretical Background
		3.1 Restricted Boltzmann Machines
		3.2 Dropout-Based Restricted Boltzmann Machines
	4 Methodology
		4.1 Proposed Approach
		4.2 Experimental Setup
		4.3 Datasets
	5 Experimental Results
		5.1 Restricted Boltzmann Machines
		5.2 Deep Belief Networks
	6 Conclusion
	References
Enhancing Hyper-to-Real Space Projections Through Euclidean Norm Meta-heuristic Optimization
	1 Introduction
	2 Hypercomplex Representation
		2.1 Minkowski p-norm
	3 Meta-heuristic Optimization
	4 Methodology
		4.1 Hypercomplex Optimization
		4.2 Last Iteration Optimization
		4.3 Benchmarking Functions
		4.4 Experimental Setup
	5 Experimental Results
		5.1 Overall Discussion
		5.2 Computational Burden
		5.3 How Does p Influence Projections?
	6 Conclusion
	References
Using Particle Swarm Optimization with Gradient Descent for Parameter Learning in Convolutional Neural Networks
	1 Introduction
	2 Gradient-Based Learning in Neural Networks
	3 Particle Swarm Optimization
	4 Literature Review
	5 Experimental Setup
		5.1 MNIST Database
		5.2 Evaluation
		5.3 Hyperparameters
	6 Model
	7 Results
	8 Conclusions and Future Work
	References
Image Segmentation
Object Delineation by Iterative Dynamic Trees
	1 Introduction
	2 Iterative Dynamic Trees
		2.1 Object Delineation by Image Foresting Transform
		2.2 The IDT Algorithm
	3 Experimental Results
	4 Conclusion
	References
Low-Cost Domain Adaptation for Crop and Weed Segmentation
	1 Introduction
	2 Background
	3 Methodology
	4 Results
	5 Conclusions and Future Work
	References
Databases
MIGMA: The Facial Emotion Image Dataset for Human Expression Recognition
	1 Introduction
	2 Related Works
	3 Methodology: Proposed Dataset Environmental Protocol
	4 Results
		4.1 Dataset Properties
		4.2 Dataset Statistical Analysis
		4.3 Case-Study: Dataset Performance in a Convolutional Neural Network Framework
	5 Conclusion and Discussions
	References
Construction of Brazilian Regulatory Traffic Sign Recognition Dataset
	1 Introduction
	2 Related Works
	3 Proposed Architecture
		3.1 Image Pre-processing
		3.2 The Dataset
		3.3 CNN Architecture
	4 Results and Discussion
	5 Conclusion and Future Work
	References
Japanese Kana and Brazilian Portuguese Manuscript Database
	1 Introduction
	2 The Dataset
	3 Related Databases
	4 Experimental Settings
		4.1 Feature Extraction
		4.2 Classifiers
	5 Experimental Results and Discussion
		5.1 Writer Identification
		5.2 Syllabary Identification
	6 Concluding Remarks
	References
Skelibras: A Large 2D Skeleton Dataset of Dynamic Brazilian Signs
	1 Introduction
	2 Related Work
	3 Corpus de Libras Dataset
	4 Skelibras Dataset
	5 Baseline Classifiers
	6 Experiments
	7 Conclusion
	References
Deep Learning
Cricket Scene Analysis Using the RetinaNet Architecture
	1 Introduction
	2 Problem Background
		2.1 Related Works
	3 Dataset and Experiment Setup
	4 RetinaNet Architecture
	5 Results
	6 Discussion and Critique
	7 Conclusion
	References
Texture-Based Image Transformations for Improved Deep Learning Classification
	1 Introduction
	2 Related Work
	3 Proposed Method
	4 Datasets
	5 Evaluation and Results
		5.1 Results for KTH-TIPS2-b Dataset
		5.2 Results for Virus Dataset
	6 Conclusion
	References
Towards Precise Recognition of Pollen Bearing Bees by Convolutional Neural Networks
	1 Introduction
	2 Related Works
	3 Convolutional Neural Networks Architectures
		3.1 Transfer Learning
	4 Pollen Bearing Bees Dataset
	5 Experimental Setup
		5.1 Colour Preprocessing Techniques
	6 Results and Discussion
	7 Conclusion
	References
Web Application Attacks Detection Using Deep Learning
	1 Introduction
	2 Background and Related Work
	3 A Two-Step Learning Approach for Anomaly Detection
		3.1 Pre-training a HTTP Language Model
		3.2 One-Class Classification
	4 Results
	5 Conclusion and Further Work
	References
Less Is More: Accelerating Faster Neural Networks Straight from JPEG
	1 Introduction
	2 JPEG Compression
	3 Related Work
	4 Speeding up CNN Models Designed for DCT Input
		4.1 Reducing the Number of Channels
		4.2 Reducing the Number of Layers
	5 Experiments and Results
		5.1 Effects of Reducing the Number of Channels
		5.2 Effects of Reducing the Number of Layers
	6 Conclusion
	References
Optimizing Person Re-Identification Using Generated Attention Masks
	1 Introduction
	2 Proposed Methodology
		2.1 Network Architecture
		2.2 Loss
	3 Experimental Settings
		3.1 Data
		3.2 Data Augmentation
		3.3 Training
	4 Results and Discussion
	5 Conclusion
	References
Self-supervised Bernoulli Autoencoders for Semi-supervised Hashing*-8pt
	1 Introduction
	2 Related Works
	3 Methods
		3.1 Generative Model and Bernoulli Autoencoders
		3.2 Parametrization by Neural Nets
		3.3 Unsupervised Training
		3.4 Semi-supervised Training
		3.5 Efficient Implementation
	4 Experiments
	5 Conclusions
	References
Explainable Artificial Intelligence
Interpretable Concept Drift
	1 Introduction
	2 Related Works
	3 Visualizing Drift in Decision Trees
		3.1 Node Frequency Analysis
		3.2 Node Accuracy Analysis
	4 Interpretable Drift Detector
	5 Experiments
	6 Conclusion
	References
Interpreting a Conditional Generative Adversarial Network Model for Crime Prediction
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Dataset
		3.2 Conditional Generative Adversarial Network
		3.3 Training and Evaluation Metrics
		3.4 SHAP Values and Model Interpretation
	4 Results
		4.1 cGAN
		4.2 Analysis of SHAP Values
	5 Conclusions and Future Work
	References
Interpreting Decision Patterns in Financial Applications
	1 Introduction
	2 Background - Interpretable AI in Finance
		2.1 Interpretability Approaches
		2.2 Interpretability Models
	3 Proposed Approach
	4 Experimental Setup
		4.1 Dataset Description
		4.2 Evaluation Metrics
		4.3 Models
	5 Experimental Results and Analysis
	6 Conclusions and Future Work
	References
Image Processing
Metal Artifact Reduction Based on Color Mapping and Inpainting Techniques
	1 Introduction
	2 MAR Based on Color Mapping and Inpainting Techniques
		2.1 Tone Mapping
		2.2 Metallic Artifacts Classification
		2.3 Artifacts Geometry Evaluation
		2.4 Inpainting
		2.5 3D Reconstruction
	3 Results
		3.1 Tone Mapping Enhancement
		3.2 Structuring Element Analysis
		3.3 Reconstruction
	4 Discussion
	5 Conclusion
	References
New Improvement in Obtaining Monogenic Phase Congruency
	1 Introduction
	2 Monogenic Phase Congruency
	3 Incorrect Edge Detection in MPC
	4 Materials
	5 Problem Solution
	6 Experimental Results and Analysis
	7 Conclusions
	References
Machine Learning
Evaluating the Construction of Feature Descriptors in the Performance of the Image Data Stream Classification
	1 Introduction
	2 Background
	3 Related Works
	4 Experimental Method
	5 Experimental Evaluation
		5.1 Experimental Results
		5.2 Statistical Analysis
	6 Conclusion
	References
Clustering-Based Partitioning of Water Distribution Networks for Leak Zone Location
	1 Introduction
	2 Materials
		2.1 WDN Partitioning Strategies
	3 Methodology
		3.1 Class Formation
		3.2 a DBSCAN Variation
	4 Case Study
		4.1 Modena WDN
		4.2 Data Generation
		4.3 Sensor Configuration
	5 Results and Discussion
		5.1 Topology-Based Clustering Methods
		5.2 Hydraulics-Based Clustering Methods
		5.3 Effect of the Variable Used
	6 Conclusions
	References
Bias Quantification for Protected Features in Pattern Classification Problems
	1 Introduction
	2 Fuzzy-Rough Set Theory
	3 Similarity Function and Bias Quantification Measure
	4 Experiments, Results and Discussion
	5 Concluding Remarks
	References
Regional Commodities Price Volatility Assessment Using Self-driven Recurrent Networks
	1 Introduction
	2 Commodities Prices Prediction Models
		2.1 Problem Formulation
		2.2 Recurrent Neural Network Architecture
		2.3 Training Procedure
	3 Experiments
		3.1 Data
		3.2 Hyperparameters Selection
		3.3 International Shock Simulation
	4 Conclusions
	References
Semi-supervised Deep Learning Based on Label Propagation in a 2D Embedded Space
	1 Introduction
	2 Proposed Pipeline
		2.1 Deep Feature Learning
		2.2 Feature Space Projection
		2.3 Label Propagation
	3 Experiments and Results
		3.1 Experimental Set-Up
		3.2 Datasets
		3.3 Implementation Details
		3.4 Experimental Results
	4 Discussion
	5 Conclusion
	References
Iterative Creation of Matching-Graphs – Finding Relevant Substructures in Graph Sets
	1 Introduction and Related Work
	2 Graphs and Graph Edit Distance - Basic Definitions
	3 Matching-Graphs
		3.1 Creating Matching-Graphs
		3.2 Iterative Building of Matching-Graphs
	4 Experimental Evaluation
		4.1 Experimental Setup
		4.2 Test Results and Discussion
	5 Conclusions and Future Work
	References
Semi-Autogeonous (SAG) Mill Overload Forecasting
	1 Introduction
	2 Prediction of Overloads
		2.1 Related Work
	3 Proposed Method
		3.1 Feature Selection
		3.2 Convolutional Neural Networks and Gram Matrices
		3.3 Unbalanced Classes and Snowball Method
		3.4 Summarize as a Whole Framework
	4 Experiments and Results
	5 Conclusions and Future Works
	References
Novel Time-Frequency Based Scheme for Detecting Sound Events from Sound Background in Audio Segments
	1 Introduction
	2 Literature Review
	3 Theoretical Framework
		3.1 Wavelet Transform
		3.2 Mel-Frequency Cepstral Coefficients
		3.3 Support Vector Machine
		3.4 K-Nearest Neighbor Classifier
	4 Proposed Method
		4.1 The US-SED Dataset
		4.2 Pre-processing
		4.3 Feature Extraction
		4.4 Detection
	5 Simulation Results
	6 Conclusion
	References
Computer Vision
Generalized Conics with the Sharp Corners
	1 Introduction
	2 Generalized Conics
	3 Generalized Conics from Distance Transform
	4 Multifocal Ellipse with Corners
	5 Changing the Angle of the Egg-Shape Corner
	6 Multifocal Hyperbola with Corners
	7 Changing the Angle of the Hyperbolic Shape Corner
	8 Shape Representation with the Generalized Conics
	9 Conclusion
	References
Automatic Face Mask Detection Using a Hide and Seek Algorithm
	1 Introduction
	2 Related Work
		2.1 General Object Detection
		2.2 Convolutional Neural Networks
	3 Proposed Approach
	4 Experimentation
		4.1 Dataset
		4.2 Evaluation Metrics
	5 Result Analysis
		5.1 Visual Intuition Development
		5.2 Bias Elimination
		5.3 Confusion Matrix and It\'s Analysis
		5.4 Computational Power Comparison
		5.5 Invariant to Orientation of Face
	6 Discussion
		6.1 Facial Point Choice
	7 Conclusion and Future Works
	References
A Feature Extraction Approach Based on LBP Operator and Complex Networks for Face Recognition
	1 Introduction
	2 Complex Networks
	3 Methodology
		3.1 Materials
	4 Results and Discussion
	5 Conclusions
	References
End-to-End Deep Sketch-to-Photo Matching Enforcing Realistic Photo Generation
	1 Introduction
	2 Proposed Methodology
		2.1 Network Architecture
		2.2 Loss
	3 Experimental Settings
		3.1 Data
		3.2 Pre-processing
		3.3 Training
	4 Results and Discussion
		4.1 Realistic Generation Performance
	5 Conclusion
	References
Forensic Analysis of Tampered Digital Photos
	1 Introduction
	2 State of the Art
		2.1 Digital Forensics
		2.2 Multimedia Manipulation Techniques
		2.3 Techniques Used to Detect Photos Manipulation
	3 Architecture
		3.1 General Architecture
		3.2 Autopsy Module Architecture
	4 Experimental Setup
		4.1 Datasets
		4.2 Evaluation Metrics
	5 Results Analysis
	6 Conclusion
	References
COVID-19 Lung CT Images Recognition: A Feature-Based Approach
	1 Introduction
	2 Proposed Description and Proposed Classification Algorithm
		2.1 Lung Segmentation
		2.2 Histogram Computation
		2.3 Feature Extraction
	3 Performance Assessment
		3.1 Patients Dataset
		3.2 Classification Procedure and Results
	4 Conclusions
	References
A Topologically Consistent Color Digital Image Representation by a Single Tree
	1 Introduction
	2 Related Works
	3 Building the CRIT
	4 Conclusions and Future Work
	References
Author Index