Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Name: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications | 22nd Iberoamerican Congress, CIARP 2017, Valparaíso, Chile, November 7-10, 2017, Proceedings
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22nd Iberoamerican Congress, CIARP 2017, Valparaíso, Chile, November 7-10, 2017, Proceedings

Marcelo Mendoza Sergio Velastín(Herausgeber*in)

Springer (Verlag)

Erschienen am 9. Februar 2018

XVIII, 730 Seiten

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978-3-319-75193-1 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents
A Citation k-NN Approach for Facial Expression Recognition
1 Introduction
2 Geometrical Descriptor
3 Multiple Instance Learning and Citation-kNN
3.1 Modified Citation-kNN
3.2 Citation kNN on Bags of Time-Stamped Facial Expression Descriptors
4 Experiments and Results
5 Conclusions
References
Mining Generalized Closed Patterns from Multi-graph Collections
1 Introduction
2 Basic Concepts
3 Proposed Algorithm
4 Experiments
5 Conclusions and Future Work
References
Edge Detection Based on Digital Shape Elongation Measure
1 Introduction
2 Preliminaries
2.1 Shape Elongation Measure
3 New Method for Detecting Edges
4 Experimental Illustrations
5 Concluding Remarks
References
Mining the Criminal Data of Rio de Janeiro: Analyzing the Impact of the Pacifying Police Units Deployment
1 Introduction
2 Empirical Strategy
3 Results
4 Conclusions
References
Going Deeper on BioImages Classification: A Plant Leaf Dataset Case Study
1 Introduction
2 Background
2.1 Deep Learning
2.2 Deep Convolutional Neural Networks (DCNNs)
2.3 Transfer Learning
3 Proposed Methodology
3.1 Dataset Description
3.2 Feature Extraction
3.3 Traditional Classifiers
3.4 Inception-v3 with Transfer Learning
4 Results and Discussion
5 Conclusion
References
Benchmarking Head Pose Estimation in-the-Wild
1 Introduction
2 Benchmarking Head Pose
3 Experiments
3.1 Methodology
4 Conclusions
References
Forensic Document Examination: Who Is the Writer?
Abstract
1 Introduction
2 Forensic Handwriting Analysis
2.1 Forensic Principles and Concepts
2.2 Graphometry and Other Approaches
3 Forensic Handwriting Identification Based on Graphometry
3.1 Preprocessing
3.2 Feature Extraction
3.3 Classification
3.4 Feature Selection
4 Experimental Results and Discussion
5 Conclusion and Future Works
References
Traversability Cost Identification of Dynamic Environments Using Recurrent High Order Neural Networks for Robot Navigation
1 Introduction
2 Recurrent High Order Neural Networks
2.1 The Extended Kalman Filter (EKF) Training Algorithm
3 Cost Maps Identification Using RHONN's
3.1 Experimental Results
4 Conclusion
References
Texture Classification of Phases of Ti-6Al-4V Titanium Alloy Using Fractal Descriptors
1 Introduction
2 Titanium Alloy Properties
3 Texture Analysis for Texture Classification
3.1 Bouligand-Minkowski Fractal Dimension
3.2 Error-Based Fractal Descriptors
4 Experiments
5 Results and Discussion
6 Conclusion
References
Pyramidal Zernike Over Time: A Spatiotemporal Feature Descriptor Based on Zernike Moments
1 Introduction
2 Related Work
3 Proposed Approach
3.1 Key Frame Selection
3.2 Computation of Pyramidal Zernike Over Time
3.3 Gabor Filter Bank Computation
4 Experimental Results
5 Conclusions
References
A Multilabel Extension of LDA Based on the Gram-Schmidt Orthogonalization Procedure
1 Introduction
2 Proposed Method: ML-GS-LDA
3 Methodology
3.1 Validation
4 Results and Discussion
5 Conclusions
References
Linear Modelling of Cerebral Autoregulation System Using Genetic Algorithms
Abstract
1 Introduction
2 Methods
2.1 CA Modelling by Using SVM
2.2 Proposed Model Resistive-Capacitive R-C
2.3 Subjects and Measurements
3 Results
4 Discussion
5 Conclusions
References
Knowledge Transfer for Writer Identification
1 Introduction
2 Knowledge Transfer with Dissimilarity
3 Databases and Feature Extraction
4 Experimental Results and Discussion
5 Conclusion
References
Real-Time Brand Logo Recognition
1 Introduction
2 Related Works
3 Deep Convolutional Neural Networks
3.1 Single Shot MultiBox Detector
4 Our Approaches and Contributions
4.1 Transfer Learning Methodology
4.2 Our Proposal Approaches
5 Experiments
5.1 DataSet
5.2 Comparison of Our Approaches
5.3 Comparison Against Other Researches
6 Conclusion
References
Retinal Vessels Segmentation Based on a Convolutional Neural Network
1 Introduction and Background
2 The Method
3 Experiments
3.1 Training Strategy and Parameters Setting
3.2 Results
4 Conclusion
References
DNLM-IIFFT: An Implementation of the Deceived Non Local Means Filter Using Integral Images and the Fast Fourier Transform for a Reduced Computational Cost
1 Introduction
2 Background
3 Proposed Method: DNLM-IFFT
3.1 Integral Images
4 Correlation and the Fast Fourier Transform
5 Experiments and Results
6 Conclusions and Future Work
References
Utilizing Deep Learning and 3DLBP for 3D Face Recognition
1 Introduction
2 Preprocessing and Local Features
2.1 Symmetric Filling
2.2 Iterative Closest Point
2.3 Savitzky-Golay Filter
2.4 3DLBP Features
3 Convolutional Neural Network
4 Proposed Method
4.1 Data Preprocessing
4.2 Generation of Depth Maps from the Point Cloud
4.3 Feature Extraction
4.4 Matching
5 EURECOM Kinect Dataset
6 Experimental Results
7 Conclusion
References
Efficient Hyperparameter Optimization in Convolutional Neural Networks by Learning Curves Prediction
1 Introduction
2 Materials and Methods
2.1 Construction of the Neural Network
2.2 Obtaining the Learning Curves
2.3 Learning Curves Smoothing
2.4 Learning Curves Forecasting
2.5 Hyperparameters Optimization
3 Experimental Setup
3.1 Datasets
3.2 Methodology
4 Results and Discussion
5 Conclusions and Future Work
References
Evaluation of Deep Feedforward Neural Networks for Classification of Diffuse Lung Diseases
1 Introduction
2 Deep Feedforward Neural Networks
3 Materials and Related Work
4 Methods
5 Results and Discussion
5.1 Results of Dimensionality Reduction Methods
5.2 Results of Classification
6 Conclusion
References
Non-dermatoscopic Image Analysis for the Recognition of Malignant Skin Diseases with Convolutional Neural Network and Autoencoders
1 Introduction
2 Background
2.1 Convolutional Neural Network (CNN)
2.2 Classification by Reconstruction
3 Datasets
4 Proposed Method
4.1 Data Preprocessing
4.2 Features Extractor and Classifier
4.3 Clasification with Autoencoders
5 Results
6 Conclusions
References
Non-stationary Multi-output Gaussian Processes for Enhancing Resolution over Diffusion Tensor Fields
1 Introduction
2 Materials and Methods
2.1 dMRI and Tensor Fields
2.2 Feature-Based Interpolation Framework
2.3 Multi-output Gaussian Processes and Non-stationary Kernel
2.4 Experimental Setup and Datasets
3 Experimental Results and Discussion
3.1 Crossing Fibers
3.2 Real DT Field
4 Conclusions and Future Work
References
Improving the Classification of Volcanic Seismic Events Extracting New Seismic and Speech Features
Abstract
1 Volcanic Seismology and Pattern Recognition
2 Materials and Methods
2.1 Classified Database
2.2 Feature Extraction
2.3 Classification
2.4 Feature Selection
3 Results
4 Discussion and Conclusions
Acknowledgements
References
An Automatic System for Computing Malaria Parasite Density in Thin Blood Films
1 Introduction
1.1 Related Work
2 Proposed Method
2.1 Image Acquisition
2.2 Image Preprocessing
2.3 Connected Component Analysis
2.4 Detecting Infected Cells
3 Experimental Results
4 Conclusion
References
A Local Branching Heuristic for the Graph Edit Distance Problem
1 Introduction
2 GED Definition and MILPJH Model
3 Local Branching Heuristic for GED
4 Computational Experiment
5 Conclusion
References
Emotion Assessment by Variability-Based Ranking of Coherence Features from EEG
1 Introduction
2 Variability-Based Ranking of the Coherence Features
3 Experiments and Results
4 Conclusions
References
Fusion of Deep Learning Descriptors for Gesture Recognition
1 Introduction
2 Method Overview
2.1 Record Gesture Information
2.2 Keyframe Extraction Method
2.3 Feature Extraction
2.4 Fusion Methods
3 Experiments and Results
3.1 Fusion Methods Evaluation
4 Conclusion
References
Ultimate Leveling Based on Mumford-Shah Energy Functional Applied to Plant Detection
1 Introduction
2 Theoretical Background
3 Ultimate Levelings Based on Energy Functions
3.1 Filtering Based on Mumford-Shah Energy
4 Results and Experiments
5 Conclusion
References
Sclera Segmentation in Face Images Using Image Foresting Transform
1 Introduction
2 Methodology
2.1 Eye Location
2.2 Sclera Segmentation
3 Results and Discussion
3.1 Image Databases
3.2 Experiments on the Eye Localization Method
3.3 Experiments on the Sclera Segmentation Method
4 Conclusions
References
Use of Machine Learning to Improve the Robustness of Spatial Estimation of Evapotranspiration
1 Introduction
2 Materials and Methods
2.1 Ground Data and Images
2.2 Objects Anchor Selection
2.3 METRIC Model with GEOBIA Approach
2.4 Validation Process
3 Results and Discussion
3.1 Training and Classification
3.2 METRIC Model with GEOBIA Approach
4 Conclusions
References
Automatic Peripheral Nerve Segmentation in Presence of Multiple Annotators
1 Introduction
2 Materials and Methods
2.1 Multi-annotator Classifications Schemes
3 Results and Discussions
4 Conclusion
References
Sparse Hilbert Embedding-Based Statistical Inference of Stochastic Ecological Systems
1 Introduction
2 Sparse Hilbert Space Embedding-Based Distance for Approximate Bayesian Computation
3 Experiments
4 Conclusions
References
Fingerprint Presentation Attack Detection Method Based on a Bag-of-Words Approach
1 Introduction
2 Proposed Method
3 Experimental Evaluation
3.1 Experimental Protocol
3.2 Experimental Results
4 Conclusions
References
Multi-objective Overlapping Community Detection by Global and Local Approaches
1 Introduction
2 The MOGLAOC Algorithm
2.1 General Steps of MOGLAOC
2.2 Expansion, Improving and Merging Steps
3 Experimental Results
4 Conclusions
References
Impulse Response Estimation of Linear Time-Invariant Systems Using Convolved Gaussian Processes and Laguerre Functions
1 Introduction
2 Convolved Gaussian Processes
3 Laguerre Functions
4 Proposed Method
4.1 Hyperparameter Learning
5 Results
5.1 Approximation of the Impulse Response
5.2 Prediction of Missing Input/Output Values
6 Discussion and Future Work
References
A Novel Hybrid Data Reduction Strategy and Its Application to Intrusion Detection
1 Introduction
2 Related Work
3 Our Proposal
4 Experimental Results
5 Conclusions
References
Clustering-Based Undersampling to Support Automatic Detection of Focal Cortical Dysplasias
1 Introduction
2 Methods
2.1 MRI Feature Estimation for Automatic Detection of Dysplasias
2.2 Relevant Sampling for Imbalance Problem in Dysplasias Recognition
2.3 Bagging Approach
3 Experimental Setup
4 Results and Discussion
5 Conclusions
References
Ultrasonic Assessment of Platelet-Rich Plasma by Digital Signal Processing Techniques
Abstract
1 Introduction
2 Materials and Method
2.1 Hematological Samples
2.2 Characterization System
2.3 Ultrasonic Inspection
2.4 Computational Procedures
3 Results
4 Conclusions
References
3D Probabilistic Morphable Models for Brain Tumor Segmentation
1 Introduction
2 Materials and Methods
2.1 Database
2.2 3D Brain Tumor Model
3 Results and Discussions
3.1 Training Results for 3D-MM
3.2 Fitting Results
4 Conclusions and Future Works
References
Multi Target Tracking Using Determinantal Point Processes
1 Introduction
2 Determinantal Point Processes
2.1 Optimization Step
3 PHD Filter - DPP Algorithm Description
4 Experiments
4.1 Experimental Settings
4.2 Evaluation Results
5 Conclusion
References
Boosted Projection: An Ensemble of Transformation Models
1 Introduction
2 Proposed Approach
3 Experimental Results
3.1 Pedestrian Detection
3.2 Image Classification
4 Conclusions
References
Full-Quaternion Color Correction in Images for Person Re-identification
1 Introduction
2 Algebra of the Quaternions
3 The Proposed Approach
3.1 Full-Quaternion
3.2 Hyperbolic Cosine and Fourier Transforms
3.3 Visualization
4 Experimental Results
5 Conclusions
References
Long Short-Term Memory Networks Based in Echo State Networks for Wind Speed Forecasting
1 Introduction
2 Echo State Network and Long Short-Term Memory Network
3 Proposal
4 Experiments and Results
5 Conclusions and Future Work
References
On the Use of Pre-trained Neural Networks for Different Face Recognition Tasks
1 Introduction
2 Using a Pre-trained Network for Face Recognition
2.1 FV-DCNN
2.2 Bilinear Model
3 Using a Pre-trained Network for Heterogeneous Face Recognition
4 Experimental Analysis
4.1 Performance Evaluation for Face Recognition
4.2 Performance Evaluation for Face Sketch Recognition
5 Conclusions
References
Many-Objective Ensemble-Based Multilabel Classification
1 Introduction
2 Multiobjective Optimization
3 Statistical Model
4 Stacking and Proposed Methodology
5 Experimental Setting
5.1 Definition of Datasets and Evaluation Metrics
5.2 Contenders for a Comparative Analisys and Versions of the Proposed Method
6 Results
7 Concluding Remarks
References
-1Bio-Chemical Data Classification by Dissimilarity Representation and Template Selection
1 Introduction
2 Materials and Methods
3 Dissimilarity Representations
4 Entropy-Based Template Selection
5 Experimental Results and Discussion
6 Conclusions and Future Work
References
Abnormal Event Detection in Video Using Motion and Appearance Information
1 Introduction
2 Related Works
3 Proposed Method
3.1 Feature Extraction
3.2 Abnormal Event Detection
4 Experimental Results
5 Conclusions
References
Efficient and Effective Face Frontalization for Face Recognition in the Wild
1 Introduction
2 Related Work
2.1 3D Face Modeling from a Single 2D Image
2.2 Filling of Self-occluded Regions
3 Proposal
3.1 Efficient Dense 3D Mesh Construction
3.2 Symmetric Interpolation for Self-occlusion
4 Experimental Evaluation
4.1 Computational Efficiency Experiments
5 Conclusions
References
Path-Gradient - A Theory of Computing Full Intensity-Transition Between Two Points
Abstract
1 Introduction
2 Theory and Algorithms
2.1 Definition of Path-Gradient and Regularized Path-Gradient
2.2 Algorithms
3 Experimental Results
4 Conclusions
Acknowledgements
References
A Robust Indoor Scene Recognition Method Based on Sparse Representation
1 Introduction
2 Methodology
3 Experiments
4 Conclusion
References
Deep Convolutional Neural Networks and Noisy Images
1 Introduction
1.1 Related Work
2 Experiments
2.1 Experimental Setup
2.2 Datasets
3 Results and Discussion
4 Conclusions
References
Spiking Hough for Shape Recognition
1 Introduction
2 Spiking Hough Multi-class Classification System
2.1 Spiking Neural Network Model
2.2 Hough Transform Analysis
2.3 Spiking Hough for Feature Extraction
2.4 Supervised Classification
3 Experiments and Results
4 Conclusions
References
Region-Based Classification of PolSAR Data Through Kernel Methods and Stochastic Distances
1 Introduction
2 Stochastic Distances for PolSAR Data
3 Region-Based Classification and Kernel Methods
4 Experiments and Results
5 Conclusions
References
Hand Posture Recognition Using Convolutional Neural Network
1 Introduction
2 Method Overview
3 Gesture Dataset
4 Hand Detection and Wrist Localization
4.1 Hand Detection
4.2 Wrist Localization
5 Hand Posture Recognition
5.1 Gabor Filter
5.2 Convolutional Neural Network
6 Experimental Results
7 Conclusions
References
On Semantic Solutions for Efficient Approximate Similarity Search on Large-Scale Datasets
1 Introduction
2 Locality Sensitive Hashing
2.1 Fractal Theory
3 Deep Fractal Based Hashing - DAsH
3.1 Using Fractals to Estimate LSH Parameters
4 Experiments
4.1 Experiment 1: Tunning LSH Parameters
4.2 Retrieval Performance
5 Conclusions
References
Self-organizing Maps for Motor Tasks Recognition from Electrical Brain Signals
1 Introduction
2 Methods and Materials
2.1 EEG Data Description
2.2 Feature Extraction and Selection
2.3 Self-organizing Maps (SOM)
2.4 Performance Evaluation
3 Results
4 Conclusions
References
Semantic Segmentation of Color Eye Images for Improving Iris Segmentation
1 Introduction
2 Proposed Method
2.1 Semantic Segmentation Algorithm
2.2 Manual Annotation of Eye Images
3 Experimental Results
4 Conclusions
References
A Single-Step 2D Thinning Scheme with Deletion of P-Simple Points
1 Introduction
2 Basic Notions and Results
3 Linking P-Simple Points and Our Sufficient Conditions
4 New Sufficient Conditions
5 A Single-Step 2D Thinning Scheme
References
Non Local Means Image Filtering Using Clustering
1 Introduction
2 Review of Non Local Means Image Filter
3 NLM and Random Sampling
4 Non Local Means over Clusters of Patches
4.1 Non Local Means Using Clusters
4.2 Clustering of Patches
5 Proposed Methods
6 Results
7 Conclusions
References
Neural Networks for the Reconstruction and Separation of High Energy Particles in a Preshower Calorimeter
1 Introduction
2 Preshower Detector
3 Reconstruction Algorithm
4 Neural Networks for Particle Separation
5 Experiments
6 Conclusions
References
Noisy Character Recognition Using Deep Convolutional Neural Networks
1 Introduction
2 Theoretical Background
2.1 Learning Filters (LF)
2.2 Architecture Optimization (AO)
3 Experimental Results
3.1 Datasets
3.2 Experiments
3.3 Discussion
4 Conclusions
References
A Flexible Framework for the Evaluation of Unsupervised Image Annotation
1 Introduction
2 Evaluation Framework for UAIA
2.1 Measuring Coverage and Relevance in UAIA Methods
2.2 Measuring the Semantic Relatedness
3 Experiments and Results
3.1 Dataset, Methods and Experimental Settings
3.2 Evaluating Proposed Metrics
3.3 How Relevant Are the Words at Different Thresholds?
4 Conclusions
References
Unsupervised Local Regressive Attributes for Pedestrian Re-identification
1 Introduction
2 Our Approach
2.1 Proposed Method
3 Experiments
3.1 Transfer Learning
3.2 Pedestrian Re-identification
4 Conclusions
References
A Deep Boltzmann Machine-Based Approach for Robust Image Denoising
1 Introduction
2 Restricted Boltzmann Machines
2.1 Deep Boltzmann Machines
3 Proposed Approach
4 Experiments and Discussion
5 Conclusion
References
Discovering Bitcoin Mixing Using Anomaly Detection
1 Introduction
2 Discovering Bitcoin Mixing
3 Experiments
4 Conclusions
References
A Scale-Space Approach for Multiscale Shape Analysis
1 Introduction
2 Scale-Space BAS and MFD
3 Experimental Results
3.1 Experiments on MPEG-7 Part B Shape Dataset
3.2 Experiments on Kimia-216 Shape Dataset
4 Discussion and Conclusion
References
An Unsupervised Approach for Eye Sclera Segmentation
1 Introduction
2 The Method
3 Results
4 Conclusions
References
An Approach to Clustering Using the Expectation-Maximization and Selection of Attributes ReliefF Applied to Water Treatment Plants process
1 Introduction
2 Theoretical Background
2.1 Expectation-Maximization (EM) Algorithm
2.2 ReliefF Algorithm
3 Materials e Methods
3.1 Characteristics of the Studied Process
3.2 Computational Experiments
4 Results and Discussions
5 Conclusion
References
A Two-Step Neural Network Approach to Passage Retrieval for Open Domain Question Answering
1 Introduction
2 Related Work
3 Model Description
3.1 Step 1. Preprocess Data
3.2 Step 2. Calculate Similarity Matrix
3.3 Step 3. Convolutional Model
3.4 Step 4 and 5. Two Ranking Stages
4 Experimental Setup
4.1 Test Datasets
4.2 Baseline Models
5 Results
6 Conclusions
References
Ensembles of Multiobjective-Based Classifiers for Detection of Epileptic Seizures
1 Introduction
2 Feature Extraction
3 Learning Machines
3.1 Multinomial Logistic Regression
3.2 Multinomial Logistic Regression for Transfer Learning
3.3 Model Selection and Ensembles
3.4 Proposed Methodologies
4 Experiments
4.1 Definition of Training, Validation and Test Sets for Source and Target Patients
4.2 Performance Metrics and Developed Comparison Benchmarks
5 Results
6 Analysis
7 Conclusion
References
Class Confusability Reduction in Audio-Visual Speech Recognition Using Random Forests
1 Introduction
2 Class Confusability
3 Classification Based on Absent Classes
4 Proposed Approach
5 Audio-Visual Databases
6 Experimental Results
7 Conclusions
References
Exploring Image Bit Planes for Video Shot Boundary Detection
1 Introduction
2 Methodology
3 Experimental Results
3.1 Data Sets
3.2 Evaluation Metrics
3.3 Parameter Settings
3.4 Results
4 Conclusions
References
Convolutional Network for EEG-Based Biometric
1 Introduction
2 Approach
2.1 Physionet EEG Database
2.2 Methodology
3 Experimental Results and Discussion
4 Conclusions
References
Skeleton Pruning Based on Elongation and Size of Object's Limbs and Boundary's Convexities
Abstract
1 Introduction
2 Basic Notions
3 The Method
4 Conclusion
References
Volume Rendering by Stochastic Neighbor Embedding-Based 2D Transfer Function Building
1 Introduction
2 Theoretical Background
3 Experiments and Results
4 Conclusions
References
Text Localization in Born-Digital Images of Advertisements
1 Introduction
2 Related Work
3 Database
3.1 Advertisement Database
4 Our Approach
4.1 Edge-Based Morphological Growing
4.2 Stroke Width Transform
4.3 Extremal Regions
4.4 Combination of Masks
5 Results
6 Conclusion
References
Deep Learning Techniques Applied to the Cattle Brand Recognition
Abstract
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Image Database Selection
3.2 Model Selection of a Pre-trained CNN
3.3 Image Pre-processing and CNN Application
3.4 Image Feature Extraction
3.5 Training and Classification of Images with Support Vector Machines
3.6 Assessment of Classification Results - Confusion Matrix
4 Results and Discussions
5 Conclusion
References
Efficient Transfer Learning for Robust Face Spoofing Detection
1 Introduction
2 Face Spoofing Detection
3 Convolutional Neural Networks (CNN)
4 Proposed Approach
4.1 Face Detection, Normalization and Deep Features Extraction
4.2 SVM Training and Threshold Calibration
4.3 Testing
5 Experiments, Results and Discussion
6 Conclusion
References
A Kernel-Based Optimum-Path Forest Classifier
1 Introduction
2 Optimum-Path Forest
2.1 Training
2.2 Classification
3 Proposed Approach
4 Methodology and Experiments
5 Conclusions
References
A Possibilistic c-means Clustering Model with Cluster Size Estimation
1 Introduction
2 Background
3 Methods
4 Results and Discussion
5 Conclusions
References
Randomized Neural Network Based Signature for Classification of Titanium Alloy Microstructures
1 Introduction
2 Metalography and Titanium Alloy
3 Texture Analysis Using Randomized Neural Network
3.1 Random Neural Network
3.2 Randomized Neural Network Based Signature
4 Experiments
5 Results and Discussion
6 Conclusion
References
Pap-smear Image Classification Using Randomized Neural Network Based Signature
1 Introduction
2 Randomized Neural Network and its Texture Signature
2.1 Randomized Neural Network Texture Signature
3 Experiments
3.1 Pap-smear database
3.2 Classification Procedure
4 Results and Discussion
5 Conclusion
References
Estimation of Pedestrian Height Using Uncalibrated Cameras
1 Introduction
2 Estimation of the Horizon and Relative Height
3 Silhouette Quality Process
3.1 Shape Matching Algorithm
3.2 Prototype Selection
4 Estimation of the Real Height
5 Experimental Results
6 Conclusions
References
Semi-supervised Online Kernel Semantic Embedding for Multi-label Annotation
1 Introduction
2 Multi-label Annotation Based on Semantic Embedding Methods
3 Semi-supervised Online Kernel Matrix Factorization for Multi-label Annotation
4 Experiments and Results
5 Conclusions
References
Ultrasonic Backscatter Signal Processing Technique for the Characterization of Animal Lymph Node
Abstract
1 Introduction
2 Theoretical Fundament
3 Ultrasonic Tissue Characterization System
3.1 Biological Samples and Ultrasonic Signal Processing
4 Conclusions
References
A Distributed Shared Nearest Neighbors Clustering Algorithm
1 Introduction
2 State of the Art
2.1 Main Contributions on Parallel Clustering Algorithms
2.2 Distributed Approaches for Clustering Based on Prototypes
3 Proposal
4 Experiments
5 Concluding Remarks
References
Automatic Classification of Optical Defects of Mirrors from Ronchigram Images Using Bag of Visual Words and Support Vector Machines
1 Introduction
2 Methodology
2.1 Ronchigram Image Acquisition
2.2 Local Image Feature Extraction (SIFT)
2.3 Image Representation via Bag of Visual Words (BoVW)
2.4 Image Classification via Support Vector Machine (SVM)
3 Experimental Evaluation
3.1 Ronchigram Image Dataset Description
3.2 Experimental Setup
3.3 Results
4 Conclusions and Future Work
References
Author Index

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