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Artificial Neural Networks in Pattern Recognition : 6th IAPR TC 3 International Workshop, ANNPR 2014, Montreal, QC, Canada, October 6-8, 2014, Proceedings / edited by Neamat El Gayar, Friedhelm Schwenker, Cheng Suen.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 8774
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 8774
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Pattern recognition systems.
- Data mining.
- Computer vision.
- User interfaces (Computer systems).
- Human-computer interaction.
- Computer science.
- Artificial Intelligence.
- Automated Pattern Recognition.
- Data Mining and Knowledge Discovery.
- Computer Vision.
- User Interfaces and Human Computer Interaction.
- Theory of Computation.
- Local Subjects:
- Artificial Intelligence.
- Automated Pattern Recognition.
- Data Mining and Knowledge Discovery.
- Computer Vision.
- User Interfaces and Human Computer Interaction.
- Theory of Computation.
- Physical Description:
- 1 online resource (XII, 289 pages) : 82 illustrations
- Edition:
- 1st ed. 2014.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2014.
- System Details:
- text file PDF
- Summary:
- This book constitutes the refereed proceedings of the 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the latest research, results, and ideas in these areas.
- Contents:
- A Decorrelation Approach for Pruning of Multilayer Perceptron Networks
- Entity Recognition
- Incremental Feature Selection by Block Addition and Block Deletion Using Least Squares SVRs
- Low-dimensional Data Representation in Data Analysis
- Analyzing dynamic ensemble selection techniques using dissimilarity Analysis
- Hidden Markov Models Based on Generalized Dirichlet Mixtures for Proportional Data Modeling
- Majority-Class aware Support Vector Domain Oversampling for Imbalanced Classification Problems
- Forward and Backward Forecasting Ensembles for the Estimation of Time Series Missing Data
- Dynamic Weighted Fusion of Adaptive Classifier Ensembles Based on Changing Data Streams: Combining Bipartite Graph Matching and Beam Search for Graph Edit Distance Approximation
- Computing Upper and Lower Bounds of Graph Edit Distance in Cubic Time
- Linear contrast classifiers in high-dimensional spaces
- A new multi-class fuzzy support vector machine algorithm
- A reinforcement learning algorithm to train a Tetris playing agent
- Bio-inspired optic ow from event-based neuromorphic sensor input
- Comparative Study of Feature Selection for White Blood Cell End-Shape Recognition for Arabic Handwritten Text Segmentation
- Intelligent Ensemble Systems for Modeling NASDAQ Microstructure: A Comparative Study
- Face Recognition based on Discriminative Dictionary with Multilevel Feature Fusion
- Ensembles in Ubiquitous Healthcare Systems.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-319-11656-3
- 9783319116563
- Access Restriction:
- Restricted for use by site license.
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