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Advances in Intelligent Data Analysis XVIII

Overview of attention for book
Cover of 'Advances in Intelligent Data Analysis XVIII'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder
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    Chapter 2 Dual Sequential Variational Autoencoders for Fraud Detection
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    Chapter 3 A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks
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    Chapter 4 Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams
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    Chapter 5 GraphMDL: Graph Pattern Selection Based on Minimum Description Length
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    Chapter 6 Towards Content Sensitivity Analysis
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    Chapter 7 Gibbs Sampling Subjectively Interesting Tiles
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    Chapter 8 Even Faster Exact k -Means Clustering
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    Chapter 9 Ising-Based Consensus Clustering on Specialized Hardware
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    Chapter 10 Transfer Learning by Learning Projections from Target to Source
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    Chapter 11 Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs
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    Chapter 12 Evaluation of CNN Performance in Semantically Relevant Latent Spaces
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    Chapter 13 Vouw: Geometric Pattern Mining Using the MDL Principle
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    Chapter 14 A Consensus Approach to Improve NMF Document Clustering
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    Chapter 15 Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams
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    Chapter 16 Widening for MDL-Based Retail Signature Discovery
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    Chapter 17 Addressing the Resolution Limit and the Field of View Limit in Community Mining
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    Chapter 18 Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics
  20. Altmetric Badge
    Chapter 19 Adversarial Attacks Hidden in Plain Sight
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    Chapter 20 Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code
  22. Altmetric Badge
    Chapter 21 Overlapping Hierarchical Clustering (OHC)
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    Chapter 22 Digital Footprints of International Migration on Twitter
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    Chapter 23 Percolation-Based Detection of Anomalous Subgraphs in Complex Networks
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    Chapter 24 A Late-Fusion Approach to Community Detection in Attributed Networks
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    Chapter 25 Reconciling Predictions in the Regression Setting: An Application to Bus Travel Time Prediction
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    Chapter 26 A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization
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    Chapter 27 Actionable Subgroup Discovery and Urban Farm Optimization
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    Chapter 28 AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model
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    Chapter 29 Detection of Derivative Discontinuities in Observational Data
  31. Altmetric Badge
    Chapter 30 Improving Prediction with Causal Probabilistic Variables
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    Chapter 31 DO-U-Net for Segmentation and Counting
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    Chapter 32 Enhanced Word Embeddings for Anorexia Nervosa Detection on Social Media
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    Chapter 33 Event Recognition Based on Classification of Generated Image Captions
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    Chapter 34 Human-to-AI Coach: Improving Human Inputs to AI Systems
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    Chapter 35 Aleatoric and Epistemic Uncertainty with Random Forests
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    Chapter 36 Master Your Metrics with Calibration
  38. Altmetric Badge
    Chapter 37 Supervised Phrase-Boundary Embeddings
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    Chapter 38 Predicting Remaining Useful Life with Similarity-Based Priors
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    Chapter 39 Orometric Methods in Bounded Metric Data
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    Chapter 40 Interpretable Neuron Structuring with Graph Spectral Regularization
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    Chapter 41 Comparing the Preservation of Network Properties by Graph Embeddings
  43. Altmetric Badge
    Chapter 42 Making Learners (More) Monotone
  44. Altmetric Badge
    Chapter 43 Combining Machine Learning and Simulation to a Hybrid Modelling Approach: Current and Future Directions
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    Chapter 44 LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-label Classification
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    Chapter 45 Angle-Based Crowding Degree Estimation for Many-Objective Optimization
Attention for Chapter 31: DO-U-Net for Segmentation and Counting
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (59th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
5 Mendeley
Summary X Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
DO-U-Net for Segmentation and Counting
Chapter number 31
Book title
Advances in Intelligent Data Analysis XVIII
Published in
Lecture notes in computer science, April 2020
DOI 10.1007/978-3-030-44584-3_31
Book ISBNs
978-3-03-044583-6, 978-3-03-044584-3
Authors

Toyah Overton, Allan Tucker, Overton, Toyah, Tucker, Allan

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 40%
Student > Ph. D. Student 1 20%
Unknown 2 40%
Readers by discipline Count As %
Computer Science 2 40%
Biochemistry, Genetics and Molecular Biology 1 20%
Unknown 2 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 August 2021.
All research outputs
#8,313,998
of 24,892,887 outputs
Outputs from Lecture notes in computer science
#2,523
of 8,151 outputs
Outputs of similar age
#155,213
of 379,179 outputs
Outputs of similar age from Lecture notes in computer science
#4
of 9 outputs
Altmetric has tracked 24,892,887 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 8,151 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has gotten more attention than average, scoring higher than 69% 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 379,179 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.

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