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Pattern Recognition

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Cover of 'Pattern Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Learned Collaborative Stereo Refinement
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    Chapter 2 Plane Completion and Filtering for Multi-View Stereo Reconstruction
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    Chapter 3 Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift
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    Chapter 4 3D Bird’s-Eye-View Instance Segmentation
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    Chapter 5 Classification-Specific Parts for Improving Fine-Grained Visual Categorization
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    Chapter 6 Adjustment and Calibration of Dome Port Camera Systems for Underwater Vision
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    Chapter 7 Training Auto-Encoder-Based Optimizers for Terahertz Image Reconstruction
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    Chapter 8 Joint Viewpoint and Keypoint Estimation with Real and Synthetic Data
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    Chapter 9 Non-causal Tracking by Deblatting
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    Chapter 10 Group Pruning Using a Bounded- $$\ell _p$$ ℓ p Norm for Group Gating and Regularization
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    Chapter 11 On the Estimation of the Wasserstein Distance in Generative Models
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    Chapter 12 Deep Archetypal Analysis
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    Chapter 13 Single Level Feature-to-Feature Forecasting with Deformable Convolutions
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    Chapter 14 Predicting Landscapes from Environmental Conditions Using Generative Networks
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    Chapter 15 Semi-supervised Segmentation of Salt Bodies in Seismic Images Using an Ensemble of Convolutional Neural Networks
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    Chapter 16 Entrack: A Data-Driven Maximum-Entropy Approach to Fiber Tractography
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    Chapter 17 Generative Aging of Brain MR-Images and Prediction of Alzheimer Progression
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    Chapter 18 Nonlinear Causal Link Estimation Under Hidden Confounding with an Application to Time Series Anomaly Detection
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    Chapter 19 Iris Verification with Convolutional Neural Network and Unit-Circle Layer
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    Chapter 20 SDNet: Semantically Guided Depth Estimation Network
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    Chapter 21 Object Segmentation Using Pixel-Wise Adversarial Loss
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    Chapter 22 Visual Coin-Tracking: Tracking of Planar Double-Sided Objects
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    Chapter 23 Exploiting Attention for Visual Relationship Detection
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    Chapter 24 Learning Task-Specific Generalized Convolutions in the Permutohedral Lattice
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    Chapter 25 Achieving Generalizable Robustness of Deep Neural Networks by Stability Training
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    Chapter 26 2D and 3D Segmentation of Uncertain Local Collagen Fiber Orientations in SHG Microscopy
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    Chapter 27 Points2Pix: 3D Point-Cloud to Image Translation Using Conditional GANs
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    Chapter 28 MLAttack: Fooling Semantic Segmentation Networks by Multi-layer Attacks
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    Chapter 29 Not Just a Matter of Semantics: The Relationship Between Visual and Semantic Similarity
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    Chapter 30 DynGraph: Visual Question Answering via Dynamic Scene Graphs
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    Chapter 31 Training Invertible Neural Networks as Autoencoders
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    Chapter 32 Weakly Supervised Learning of Dense Semantic Correspondences and Segmentation
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    Chapter 33 A Neural-Symbolic Architecture for Inverse Graphics Improved by Lifelong Meta-learning
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    Chapter 34 Unsupervised Multi-source Domain Adaptation Driven by Deep Adversarial Ensemble Learning
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    Chapter 35 Time-Frequency Causal Inference Uncovers Anomalous Events in Environmental Systems
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    Chapter 36 Tongue Contour Tracking in Ultrasound Images with Spatiotemporal LSTM Networks
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    Chapter 37 Localized Interactive Instance Segmentation
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    Chapter 38 Iterative Greedy Matching for 3D Human Pose Tracking from Multiple Views
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    Chapter 39 Visual Person Understanding Through Multi-task and Multi-dataset Learning
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    Chapter 40 Dynamic Classifier Chains for Multi-label Learning
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    Chapter 41 Learning 3D Semantic Reconstruction on Octrees
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    Chapter 42 Learning to Disentangle Latent Physical Factors for Video Prediction
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    Chapter 43 Learning to Train with Synthetic Humans
Attention for Chapter 43: Learning to Train with Synthetic Humans
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Chapter title
Learning to Train with Synthetic Humans
Chapter number 43
Book title
Pattern Recognition
Published by
Springer, Cham, September 2019
DOI 10.1007/978-3-030-33676-9_43
Book ISBNs
978-3-03-033675-2, 978-3-03-033676-9
Authors

David T. Hoffmann, Dimitrios Tzionas, Michael J. Black, Siyu Tang, Hoffmann, David T., Tzionas, Dimitrios, Black, Michael J., Tang, Siyu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 27%
Student > Master 8 17%
Researcher 8 17%
Student > Bachelor 3 6%
Student > Postgraduate 2 4%
Other 3 6%
Unknown 11 23%
Readers by discipline Count As %
Computer Science 30 63%
Engineering 5 10%
Earth and Planetary Sciences 1 2%
Unknown 12 25%