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Computational intelligence paradigms in advanced pattern classification

Author: Marek R Ogiela; L C Jain
Publisher: Berlin : Springer, ©2012.
Series: Studies in computational intelligence, v. 386
Edition/Format:   Print book : EnglishView all editions and formats
Database:WorldCat
Summary:

This volume describes the application of pattern recognition and classification approaches. Methods include handwriting recognition, medical image analysis and interpretation, development of  Read more...

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Document Type: Book
All Authors / Contributors: Marek R Ogiela; L C Jain
ISBN: 9783642240485 3642240488
OCLC Number: 796076412
Notes: Formerly CIP.
Description: xi, 197 pages : illustrations ; 25 cm.
Contents: Machine generated contents note: ch. 1 Recent Advances in Pattern Classification / Lakhmi C. Jain --
1. New Directions in Pattern Classification --
References --
ch. 2 Neural Networks for Handwriting Recognition / Horst Bunke --
1. Introduction --
1.1. State-of-the-Art --
1.2. Contribution --
2. Data Processing --
2.1. General Processing Steps --
2.2. Our Online System --
2.3. Our Offline System --
3. Neural Network Based Recognition --
3.1. Recurrent Neural Networks (RNNs) --
3.2. Long Short-Term Memory (LSTM) --
3.3. Bidirectional Recurrent Neural Networks --
3.4. Connectionist Temporal Classification (CTC) --
3.5. Multidimensional Recurrent Neural Networks --
3.6. Hierarchical Subsampling Recurrent Neural Networks --
4. Experiments --
4.1.Comparison with HMMs on the IAM Databases --
4.2. Recognition Performance of MDLSTM on Contest' Data --
5. Conclusion --
References --
ch. 3 Moving Object Detection from Mobile Platforms Using Stereo Data Registration / Antonio M. Lopez --
1. Introduction. Contents note continued: 2. Related Work --
3. Proposed Approach --
3.1. System Setup --
3.2. Feature Detection and Tracking --
3.3. Robust Registration --
3.4. Frame Subtraction --
4. Experimental Results --
5. Conclusions --
References --
ch. 4 Pattern Classifications in Cognitive Informatics / Lidia Ogiela --
1. Introduction --
2. Semantic Analysis Stages --
3. Semantic Analysis vs. Cognitive Informatics --
4. Example of a Cognitive UBIAS System --
5. Conclusions --
References --
ch. 5 Optimal Differential Filter on Hexagonal Lattice / Tetsuo Shima --
1. Introduction --
2. Preliminaries --
3. Least Inconsistent Image --
4. Point Spread Function --
5. Condition for Gradient Filter --
6. Numerical Optimization --
7. Theoretical Evaluation --
7.1. Signal-to-Noise Ratio --
7.2. Localization --
8. Experimental Evaluation --
8.1. Construction of Artificial Images --
8.2. Detection of Gradient Intensity and Orientation --
8.3. Overington's Method of Orientation Detection. Contents note continued: 8.4. Relationship between Derived Filter and Staunton Filter --
8.5. Experiment and Results --
9. Discussion --
10. Summary --
References --
ch. 6 Graph Image Language Techniques Supporting Advanced Classification and Cognitive Interpretation of CT Coronary Vessel Visualizations / Mirostaw Trzupek --
1. Introduction --
2. The Classification Problem --
3. Stages in the Analysis of CT Images under a Structural Approach Utilising Graph Techniques --
4. Parsing Languages Generated by Graph Grammars --
5. Picture Grammars in Classification and Semantic Interpretation of 3D Coronary Vessels Visualisations --
5.1. Characteristics of the Image Data --
5.2. Preliminary Analysis of 3D Coronary Vascularisation Reconstructions --
5.3. Graph-Based Linguistic Formalisms in Spatial Modelling of Coronary Vessels --
5.4. Detecting Lesions and Constructing the Syntactic Analyser --
5.5. Selected Results. Contents note continued: 6. Conclusions Concerning the Advanced Classification and Cognitive Interpretation of CT Coronary Vessel Visualizations --
References --
ch. 7 A Graph Matching Approach to Symmetry Detection and Analysis / Yosi Keller --
1. Introduction --
2. Symmetries and Their Properties --
2.1. Rotational Symmetry --
2.2. Reflectional Symmetry --
2.3. Interrelations between Rotational and Reflectional Symmetries --
2.4. Discussion --
3. Previous Work --
3.1. Previous Work in Symmetry Detection and Analysis --
3.2. Local Features --
3.3. Spectral Matching of Sets of Points in Rn --
4. Spectral Symmetry Analysis --
4.1. Spectral Symmetry Analysis of Sets in Rn --
4.1.1. Perfect Symmetry and Spectral Degeneracy --
4.2. Spectral Symmetry Analysis of Images --
4.2.1. Image Representation by Local Features --
4.2.2. Symmetry Categorization and Pruning --
4.2.3.Computing the Geometrical Properties of the Symmetry --
5. Experimental Results --
5.1. Symmetry Analysis of Images. Contents note continued: 5.2. Statistical Accuracy Analysis --
5.3. Analysis of Three-Dimensional Symmetry --
5.4. Implementation Issues --
5.5. Additional Results --
6. Conclusions --
References --
ch. 8 Pattern Classification Methods for Analysis and Visualization of Brain Perfusion CT Maps / Tomasz Hachaj --
1. Introduction --
2. Interpretation of Perfusion Maps --
Long and Short Time Prognosis --
3. Image Processing and Abnormality Detection --
4. Image Registration --
4.1. Affine Registration --
4.2. FFD Registration --
4.3. Thirion's Demons Algorithm --
4.4.Comparison of Registration Algorithms --
5. Classification of Detected Abnormalities --
6. System Validation and Results --
7. Data Visualization --
Augmented Reality Environment --
7.1. Augmented Reality Environment --
7.2. Real Time Rendering of 3D Data --
7.3. Augmented Desktop --
System Performance Test --
8. Summary --
References --
ch. 9 Inference of Co-occurring Classes: Multi-class and Multi-label Classification / Tal Sobol-Shikler. Contents note continued: 1. Introduction --
2. Applications --
3. The Classification Process --
4. Data and Annotation --
5. Classification Approaches --
5.1. Binary Classification --
5.2. Multi-class Classification --
5.3. Multi-label Classification --
6. Multi-class Classification --
6.1. Multiple Binary Classifiers --
6.1.1. One-Against-All Classification --
6.1.2. One-Against-One (Pair-Wise) Classification --
6.1.3.Combining Binary Classifiers --
6.2. Direct Multi-class Classification --
6.3. Associative Classification --
7. Multi-label Classification --
7.1. Semi-supervised (Annotation) Methods --
8. Inference of Co-occurring Affective States from Non-verbal Speech --
9. Summary --
References.
Series Title: Studies in computational intelligence, v. 386
Responsibility: Marek R. Ogiela and Lakhmi C. Jain (eds.).
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   schema:description "Contents note continued: 8.4. Relationship between Derived Filter and Staunton Filter -- 8.5. Experiment and Results -- 9. Discussion -- 10. Summary -- References -- ch. 6 Graph Image Language Techniques Supporting Advanced Classification and Cognitive Interpretation of CT Coronary Vessel Visualizations / Mirostaw Trzupek -- 1. Introduction -- 2. The Classification Problem -- 3. Stages in the Analysis of CT Images under a Structural Approach Utilising Graph Techniques -- 4. Parsing Languages Generated by Graph Grammars -- 5. Picture Grammars in Classification and Semantic Interpretation of 3D Coronary Vessels Visualisations -- 5.1. Characteristics of the Image Data -- 5.2. Preliminary Analysis of 3D Coronary Vascularisation Reconstructions -- 5.3. Graph-Based Linguistic Formalisms in Spatial Modelling of Coronary Vessels -- 5.4. Detecting Lesions and Constructing the Syntactic Analyser -- 5.5. Selected Results."@en ;
   schema:description "Contents note continued: 5.2. Statistical Accuracy Analysis -- 5.3. Analysis of Three-Dimensional Symmetry -- 5.4. Implementation Issues -- 5.5. Additional Results -- 6. Conclusions -- References -- ch. 8 Pattern Classification Methods for Analysis and Visualization of Brain Perfusion CT Maps / Tomasz Hachaj -- 1. Introduction -- 2. Interpretation of Perfusion Maps -- Long and Short Time Prognosis -- 3. Image Processing and Abnormality Detection -- 4. Image Registration -- 4.1. Affine Registration -- 4.2. FFD Registration -- 4.3. Thirion's Demons Algorithm -- 4.4.Comparison of Registration Algorithms -- 5. Classification of Detected Abnormalities -- 6. System Validation and Results -- 7. Data Visualization -- Augmented Reality Environment -- 7.1. Augmented Reality Environment -- 7.2. Real Time Rendering of 3D Data -- 7.3. Augmented Desktop -- System Performance Test -- 8. Summary -- References -- ch. 9 Inference of Co-occurring Classes: Multi-class and Multi-label Classification / Tal Sobol-Shikler."@en ;
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