Artificial Neural Networks in Pattern Recognition

Table of Contents

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   Book Overview
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   Chapter 1 What’s Wrong with Computer Vision?
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   Chapter 2 Deep Learning in the Wild
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   Chapter 3 Effect of Equality Constraints to Unconstrained Large Margin Distribution Machines
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   Chapter 4 DLL: A Fast Deep Neural Network Library
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   Chapter 5 Selecting Features from Foreign Classes
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   Chapter 6 A Refinement Algorithm for Deep Learning via Error-Driven Propagation of Target Outputs
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   Chapter 7 Combining Deep Learning and Symbolic Processing for Extracting Knowledge from Raw Text
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   Chapter 8 SeNA-CNN: Overcoming Catastrophic Forgetting in Convolutional Neural Networks by Selective Network Augmentation
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    Chapter 9 Classification Uncertainty of Deep Neural Networks Based on Gradient Information
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    Chapter 10 Learning Neural Models for End-to-End Clustering
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    Chapter 11 A $$k$$ -Nearest Neighbor Based Algorithm for Multi-Instance Multi-Label Active Learning
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    Chapter 12 Manifold Learning Regression with Non-stationary Kernels
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    Chapter 13 F-Measure Curves for Visualizing Classifier Performance with Imbalanced Data
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    Chapter 14 Maximum-Likelihood Estimation of Neural Mixture Densities: Model, Algorithm, and Preliminary Experimental Evaluation
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    Chapter 15 Generating Bounding Box Supervision for Semantic Segmentation with Deep Learning
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    Chapter 16 Inductive–Transductive Learning with Graph Neural Networks
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    Chapter 17 Bounded Rational Decision-Making with Adaptive Neural Network Priors
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    Chapter 18 Feature Selection with Rényi Min-Entropy
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    Chapter 19 Extracting Gamma-Ray Information from Images with Convolutional Neural Network Methods on Simulated Cherenkov Telescope Array Data
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    Chapter 20 Automatic Hand Sign Recognition: Identify Unusuality Through Latent Cognizance
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    Chapter 21 Cascade of Ordinal Classification and Local Regression for Audio-Based Affect Estimation
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    Chapter 22 Combining Classical and Deep Learning Methods for Twitter Sentiment Analysis
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    Chapter 23 PHoG Features and Kullback-Leibler Divergence Based Ranking Method for Handwriting Recognition
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    Chapter 24 Pattern Recognition Pipeline for Neuroimaging Data
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    Chapter 25 Anomaly Pattern Recognition with Privileged Information for Sensor Fault Detection
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    Chapter 26 Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering
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    Chapter 27 Trace and Detect Adversarial Attacks on CNNs Using Feature Response Maps
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    Chapter 28 Video and Audio Data Extraction for Retrieval, Ranking and Recapitulation (VADER $$^3$$ )
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    Chapter 29 ATM Protection Using Embedded Deep Learning Solutions
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    Chapter 30 Object Detection in Floor Plan Images
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    Chapter 31 Historical Handwritten Document Segmentation by Using a Weighted Loss