Progress in Computer Recognition Systems

Name: Progress in Computer Recognition Systems
Brand: Springer
Price: 149.79 EUR
Availability: OnlineOnly

Robert Burduk Marek Kurzynski Michal Wozniak(Editor)

Springer (Publisher)

1st Edition

Published on 7. May 2019

X, 372 pages

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978-3-030-19738-4 (ISBN)

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Content

Intro
Preface
Contents
Graph Grammar Models in Syntactic Pattern Recognition
1 Introduction
2 Graph Grammars in Syntactic Pattern Recognition
3 Computational Complexity of Graph Parsers
4 Graph Parsing Schemes in Syntactic Pattern Recognition
5 Concluding Remarks
References
Computer Vision Methods for Non-destructive Quality Assessment in Additive Manufacturing
1 Introduction
2 Vision Based Monitoring of 3D Printing Process
3 Quality Assessment of 3D Printed Surfaces
3.1 Visual Feedback for Quality Monitoring
3.2 Description of Experimental Setup
3.3 Overview of Investigated Approaches
3.4 Discussion of the Most Essential Results
4 Concluding Remarks
References
Combined kNN Classifier for Classification of Incomplete Data
1 Introduction
2 Method
3 Experiment
4 Results
5 Conclusions
References
Object Detection in Design Diagrams with Machine Learning
1 Introduction
2 Related Works
3 Yolo for Object Detection in Engineering Drawings
3.1 Artificial Apros Experiments
3.2 Experiments with Real Pöyry Data
4 Learnings
5 Conclusions
References
Separation of Speech from Speech Interference Based on EGG
1 Introduction
2 Related Works
3 The Proposed System
3.1 SUV Separation from Mixture
3.2 Voiced Speech Separation
3.3 Unvoiced Speech Separation
3.4 SUV Re-synthesis
4 Dataset
5 Experiments and Results
5.1 Objective Evaluation Criteria
5.2 Subjective Evaluation Measures
6 Conclusion
References
Improving the Quality of Clustering-Based Diagnostic Rules by Lowering Dimension of the Cluster Prototypes
1 Introduction
2 Rule-Based Diagnosis Support
3 Prototype-Based Rule Premise Conditions
4 Experiments
5 Discussion and Conclusions
References
Exploiting Label Interdependencies in Multi-label Classification
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Proposed Approach
3.2 Evaluation
4 Experiments and Discussion
5 Conclusions
References
Toward Shareable Multi-abstraction-level Feature Extractor Based on a Bayesian Network
1 Introduction
1.1 Motivation
1.2 Shareable Feature Extractor
1.3 Related Work
2 Multi-abstraction-level Feature Extractor Using a Bayesian Network (MFB)
2.1 Parameter Reduction
2.2 Invariance of Pooling by Child
3 Experimental Results
3.1 Pattern Extraction Experiments
3.2 Pooling Layer Training Experiments
4 Discussion
4.1 Bidirectional Recognition of Multiple Abstraction Features
4.2 Pooling Layer Training
4.3 Disadvantages of Bidirectional Recognition
4.4 Conclusion
References
Factorization Machines for Blog Feedback Prediction
1 Introduction
2 Factorization Machines
3 Experimental Evaluation
4 Conclusions and Outlook
References
Vertical and Horizontal Data Partitioning for Classifier Ensemble Learning
1 Introduction
2 Ensemble Classification
2.1 Generating the Base Experts
2.2 Predictions of Experts
2.3 Ensemble Pruning
2.4 Combination Strategy
3 Experimental Study
3.1 Experimental Setup
3.2 Experimental Results
4 Conclusions and Future Work
References
Segmentation of Subretinal Hyperreflective Material and Pigment Epithelial Detachment Using Kernel Graph Cut
1 Introduction
2 Materials and Methods
2.1 Graph Cut Based ILM and RPE Layer Segmentation
2.2 Classification of PED and SHRM
3 Results
3.1 Evaluation Metrics
3.2 Localization of PED and SHRM
4 Conclusion
References
Road Tracking Using Deep Reinforcement Learning for Self-driving Car Applications
1 Introduction
2 Modelling
2.1 Road Tracking
2.2 Actions Codes
2.3 Proposed DRL-RT
3 Results
3.1 Training and Testing Stages
3.2 Comparisons
4 Conclusion
References
New Heuristics for TCP Retransmission Timers
1 Introduction
2 Basic Performance Metrics for RTO Algorithms
3 The Algorithms
4 Results of Experiments
5 Conclusions and Final Remarks
References
Fault-Prone Software Classes Recognition via Artificial Neural Network with Granular Dataset Balancing
1 Introduction
2 State of the Art
3 Bug Prediction Dataset
4 Principal Component Analysis
5 Data Imbalance
6 Artificial Neural Network
7 Cross-Validation
8 Experiments
9 Performance Measures
10 Results
11 Conclusions
References
Segmentation of Scanned Documents Using Deep-Learning Approach
1 Introduction
2 Previous Works
3 Algorithm Description
4 Experiments
4.1 Benchmark Datasets
4.2 Experimental Setup
4.3 Results
4.4 Comparison with State-of-the-Art Methods
5 Summary
References
cGAAM - An Algorithm for Simultaneous Feature Selection and Clustering
1 Introduction
2 cGAAM
3 Methods
4 Results and Discussion
5 Conclusion
References
Online Adaptation of Language Models for Speech Recognition
1 Introduction
2 Background on Language Model Adaptation for Speech Recognition
3 Our Proposed Method
3.1 General Pipeline
3.2 Constructing Topic-Adapted Language Models
3.3 Topic Identification
4 Experiments
4.1 Dataset for Topic Identification
4.2 Training Dataset for Speech Recognition
4.3 Test Dataset for Speech Recognition
4.4 System Training
4.5 Experimental Results and Discussions
5 Conclusion
References
Pedestrian Detection in Severe Lighting Conditions: Comparative Study of Human Performance vs Thermal-Imaging-Based Automatic System
1 Introduction
2 Related Works
2.1 Driver's Reaction Time
2.2 Technical Solutions
3 Methods and Material
3.1 Characteristics of the Obtained Test Material
3.2 Study of Human Reaction
3.3 Automatic Recognition of Human Silhouette in Thermograms
4 Experimental Results
4.1 Human Performance
4.2 Performance of Automatic Recognition Using Thermograms
5 Discussion
6 Conclusion
References
Feature Extraction and Classification of Sensor Signals in Cars Based on a Modified Codebook Approach
1 Introduction
2 Related Work
3 Data
4 Feature Extraction
4.1 Handcrafted Feature Extraction
4.2 AFS Based on the Codebook Approach
5 Classifier
6 Results
7 Conclusion and Future Work
References
A Deep Learning Approach to Recognition of the Atmospheric Circulation Regimes
1 Introduction
2 Survey of the Field
2.1 Machine Learning in Meteorology
2.2 Atmospheric Circulation Classifications
3 Modeling
3.1 Data
3.2 Model Architecture
3.3 Model Training
4 Results and Discussion
References
Deep Learning for Object Tracking in 360 Degree Videos
1 Introduction
2 Proposed Object Trackers
2.1 Image Transformation
2.2 Object Detection
2.3 Kalman Filter
2.4 Lucas-Kanade
2.5 Combination of Kalman Filter and Lucas-Kanade
3 Results
4 Conclusion
References
Texture Features for the Detection of Playback Attacks: Towards a Robust Solution
1 Introduction
2 Databases, Protocols and Data-Related Problems
3 Basic Algorithm
4 Optimization
5 Conclusions
References
Image Smoothing Using p Penalty for 0p1 with Use of Alternating Minimization Algorithm
1 Introduction
2 Solutions
2.1 The Case p=0
2.2 The Case 0&p&1
2.3 The Case p=1, TV Filtering
3 Experimental Results
3.1 Determining Stopping Criterion for the Gauss-Seidel Method
3.2 Denoising Phantom Example
3.3 Real Life Examples
4 Conclusions and Remarks
References
Deep-Based Openset Classification Technique and Its Application in Novel Food Categories Recognition
1 Introduction
2 Background and Methods
2.1 Convolutional Neural Networks
2.2 Activation Vector Data Description Model
3 Empirical Evaluations
3.1 Datasets and Protocol
3.2 Results: Performance on Known Classes
3.3 Results: Novel Classes Detection
4 Conclusions
References
Singing Power Ratio Analysis in the Context of the Influence of Warm up on Singing Voice Quality
1 Introduction
2 Literature Review
3 Material for the Study
4 Research Background
5 The Analysis and the Results
6 Conclusion
References
Evaluation of a Feature Set with Word Embeddings to Improve Named Entity Recognition on Tweets
1 Introduction
2 Data and Features
2.1 Data
2.2 Feature Set
3 Tests and Evaluation
3.1 Implementation
3.2 Test and Results
4 Conclusions
References
Introducing Action Planning to the Anticipatory Classifier System ACS2
1 Introduction
2 Anticipatory Learning Classifier Systems (ACS2)
3 Action Planning
3.1 Goal-Generator
3.2 Bidirectional Search
4 Experiments
4.1 Environments
4.2 Results
5 Conclusions
References
Supervised Classification Box Algorithm Based on Graph Partitioning
1 Introduction
2 Supervised Classification as a G-cut Problem
3 Class Cover Problem by Colored Boxes
4 A Minimal Clique Cover Box Algorithm
5 Classification Rule Based on Box Algorithm
6 Relation of Box Algorithm to the Nearest Neighbor Rule and Tree Classifiers
6.1 Relation of Box Algorithm to the Nearest Neighbor Rule
6.2 Relation of Box Algorithm to Decision Trees
7 Experimental Results
7.1 Normal Attributes
7.2 Nominal Attributes
8 Conclusions
References
Algorithm of Multidimensional Analysis of Main Features of PCA with Blurry Observation of Facility Features Detection of Carcinoma Cells Multiple Myeloma
1 Introduction
2 A Mathematical Model of PCA Analysis with Fuzzy Observation of Object Features
3 Practical Examples of Using a Fuzzy PCA Model
4 Conclusion
References
A New Benchmark Collection for Driver Fatigue Research Based on Thermal, Depth Map and Visible Light Imagery
1 Introduction
2 Proposed Approach
2.1 Characteristics of the Obtained Test Material
2.2 Characteristics of the Benchmark
2.3 TensorFlow
3 Experimental Results
4 Summary
References
Image Contrast Enhancement Based on Laplacian-of-Gaussian Filter Combined with Morphological Reconstruction
1 Introduction
2 Related Works
3 Basic Notions
3.1 Laplacian-of-Gaussian-Based Contrast Enhancement
3.2 Morphological Processing
4 Proposed Approach
5 Tests
6 Conclusions
References
Lattice Auto-Associative Memories Induced Multivariate Morphology for Hyperspectral Image Spectral-Spatial Classification
1 Introduction
2 Multivariate Mathematical Morphology
3 Lattice Auto-Associative Memories (LAAM)
4 LAAM-Supervised Ordering
4.1 LAAM's h-Mapping
4.2 One-Side LAAM h-Supervised Ordering
4.3 Background/Foreground LAAM h-Supervised Pseudo-orderings
4.4 Beucher Morphological Gradient
4.5 Unsupervised Selection of Training Sets
5 Experimental Results with Hyperspectral Images
5.1 Methodology
5.2 Pavia University Data
6 Conclusions
References
Randomized Reference Classifier with Gaussian Distribution and Soft Confusion Matrix Applied to the Improving Weak Classifiers
1 Introduction
2 Proposed Method
2.1 Preliminaries
2.2 Soft Confusion Matrix
2.3 Randomized Reference Classifier
3 Experimental Setup
4 Results and Discussion
5 Conclusions
References
Hybrid Algorithm for the Detection and Recognition of Railway Signs
1 Introduction
2 Research Methodology, Initial Analysis, Implementations and Tests
2.1 Classic Image Processing Methods
2.2 Haar Algorithm
2.3 YOLO
3 Hybrid Concept
4 Concluding Remarks
References
Combination of Linear Classifiers Using Score Function - Analysis of Possible Combination Strategies
1 Introduction
2 Proposed Method
2.1 Linear Binary Classifiers
2.2 The Proposed Method
3 Experimental Setup
4 Results and Discussion
5 Conclusions
References
Multi Sampling Random Subspace Ensemble for Imbalanced Data Stream Classification
1 Introduction
2 Related Works
3 Multi Sampling Random Subspace Ensemble
4 Experiments
4.1 Data Streams
4.2 Evaluation
5 Results
5.1 Features Test
5.2 Imbalance Ratio Test
5.3 Ranking Tests
6 Conclusions
References
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Progress in Computer Recognition Systems

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