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Pattern Recognition

Overview of attention for book
Cover of 'Pattern Recognition'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Precise and Robust Line Detection for Highly Distorted and Noisy Images
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    Chapter 2 Pixel-Level Encoding and Depth Layering for Instance-Level Semantic Labeling
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    Chapter 3 Artistic Style Transfer for Videos
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    Chapter 4 Semantically Guided Depth Upsampling
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    Chapter 5 Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates
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    Chapter 6 Convolutional Scale Invariance for Semantic Segmentation
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    Chapter 7 Convexification of Learning from Constraints
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    Chapter 8 FSI Schemes: Fast Semi-Iterative Solvers for PDEs and Optimisation Methods
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    Chapter 9 Automated Segmentation of Immunostained Cell Nuclei in 3D Ultramicroscopy Images
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    Chapter 10 Robust Interactive Multi-label Segmentation with an Advanced Edge Detector
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    Chapter 11 Contiguous Patch Segmentation in Pointclouds
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    Chapter 12 Randomly Sparsified Synthesis for Model-Based Deformation Analysis
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    Chapter 13 Depth Map Based Facade Abstraction from Noisy Multi-View Stereo Point Clouds
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    Chapter 14 Stereo Visual Odometry Without Temporal Filtering
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    Chapter 15 Large-Scale Active Learning with Approximations of Expected Model Output Changes
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    Chapter 16 A Convnet for Non-maximum Suppression
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    Chapter 17 Occlusion-Aware Depth Estimation Using Sparse Light Field Coding
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    Chapter 18 Joint Object Pose Estimation and Shape Reconstruction in Urban Street Scenes Using 3D Shape Priors
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    Chapter 19 Joint Recursive Monocular Filtering of Camera Motion and Disparity Map
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    Chapter 20 From Traditional to Modern: Domain Adaptation for Action Classification in Short Social Video Clips
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    Chapter 21 Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints
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    Chapter 22 Reduction of Point Cloud Artifacts Using Shape Priors Estimated with the Gaussian Process Latent Variable Model
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    Chapter 23 Camera-Agnostic Monocular SLAM and Semi-dense 3D Reconstruction
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    Chapter 24 Efficient Single-View 3D Co-segmentation Using Shape Similarity and Spatial Part Relations
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    Chapter 25 Fast and Accurate Micro Lenses Depth Maps for Multi-focus Light Field Cameras
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    Chapter 26 Train Detection and Tracking in Optical Time Domain Reflectometry (OTDR) Signals
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    Chapter 27 Parametric Dictionary-Based Velocimetry for Echo PIV
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    Chapter 28 Identifying Individual Facial Expressions by Deconstructing a Neural Network
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    Chapter 29 Boundary Preserving Variational Image Differentiation
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    Chapter 30 A Prediction-Correction Approach for Real-Time Optical Flow Computation Using Stereo
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    Chapter 31 Weakly-Supervised Semantic Segmentation by Redistributing Region Scores Back to the Pixels
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    Chapter 32 Learning a Confidence Measure for Real-Time Egomotion Estimation
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    Chapter 33 Learning to Select Long-Track Features for Structure-From-Motion and Visual SLAM
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    Chapter 34 Source Localization of Reaction-Diffusion Models for Brain Tumors
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    Chapter 35 Depth Estimation Through a Generative Model of Light Field Synthesis
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    Chapter 36 Coupling Convolutional Neural Networks and Hough Voting for Robust Segmentation of Ultrasound Volumes
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#9 of 7,736)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

14 news outlets
4 blogs
212 tweeters
1 patent
1 peer review site
4 Facebook pages
5 Google+ users
2 Redditors
3 video uploaders


1 Dimensions

Readers on

3 Mendeley
Pattern Recognition
Published by
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-45886-1
978-3-31-945885-4, 978-3-31-945886-1

Bodo Rosenhahn, Bjoern Andres

Twitter Demographics

The data shown below were collected from the profiles of 212 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 33%
Unknown 2 67%
Readers by discipline Count As %
Engineering 1 33%
Unknown 2 67%

Attention Score in Context

This research output has an Altmetric Attention Score of 293. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 February 2021.
All research outputs
of 17,866,836 outputs
Outputs from Lecture notes in computer science
of 7,736 outputs
Outputs of similar age
of 271,552 outputs
Outputs of similar age from Lecture notes in computer science
of 83 outputs
Altmetric has tracked 17,866,836 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,736 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 271,552 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.