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Machine Learning Paradigms

Overview of attention for book
Cover of 'Machine Learning Paradigms'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Machine Learning Paradigms: Introduction to Deep Learning-Based Technological Applications
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    Chapter 2 Vision to Language: Methods, Metrics and Datasets
  4. Altmetric Badge
    Chapter 3 Deep Learning Techniques for Geospatial Data Analysis
  5. Altmetric Badge
    Chapter 4 Deep Learning Approaches in Food Recognition
  6. Altmetric Badge
    Chapter 5 Deep Learning for Twitter Sentiment Analysis: The Effect of Pre-trained Word Embedding
  7. Altmetric Badge
    Chapter 6 A Good Defense Is a Strong DNN: Defending the IoT with Deep Neural Networks
  8. Altmetric Badge
    Chapter 7 Survey on Deep Learning Techniques for Medical Imaging Application Area
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    Chapter 8 Deep Learning Methods in Electroencephalography
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    Chapter 9 The Implementation and the Design of a Hybriddigital PI Control Strategy Based on MISO Adaptive Neural Network Fuzzy Inference System Models–A MIMO Centrifugal Chiller Case Study
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    Chapter 10 A Review of Deep Reinforcement Learning Algorithms and Comparative Results on Inverted Pendulum System
  12. Altmetric Badge
    Chapter 11 Stock Market Forecasting by Using Support Vector Machines
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    Chapter 12 An Experimental Exploration of Machine Deep Learning for Drone Conflict Prediction
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    Chapter 13 Deep Dense Neural Network for Early Prediction of Failure-Prone Students
  15. Altmetric Badge
    Chapter 14 Non-parametric Performance Measurement with Artificial Neural Networks
  16. Altmetric Badge
    Chapter 15 A Comprehensive Survey on the Applications of Swarm Intelligence and Bio-Inspired Evolutionary Strategies
  17. Altmetric Badge
    Chapter 16 Detecting Magnetic Field Levels Emitted by Tablet Computers via Clustering Algorithms
Attention for Chapter 3: Deep Learning Techniques for Geospatial Data Analysis
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
9 X users

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
42 Mendeley
Summary X Dimensions citations
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Chapter title
Deep Learning Techniques for Geospatial Data Analysis
Chapter number 3
Book title
Machine Learning Paradigms
Published in
arXiv, January 2020
DOI 10.1007/978-3-030-49724-8_3
Book ISBNs
978-3-03-049723-1, 978-3-03-049724-8
Authors

Arvind W. Kiwelekar, Geetanjali S. Mahamunkar, Laxman D. Netak, Valmik B Nikam, Kiwelekar, Arvind W., Mahamunkar, Geetanjali S., Netak, Laxman D., Nikam, Valmik B

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 14%
Researcher 6 14%
Student > Master 6 14%
Lecturer 2 5%
Lecturer > Senior Lecturer 1 2%
Other 4 10%
Unknown 17 40%
Readers by discipline Count As %
Computer Science 8 19%
Earth and Planetary Sciences 7 17%
Engineering 3 7%
Environmental Science 2 5%
Unspecified 1 2%
Other 3 7%
Unknown 18 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 14 December 2020.
All research outputs
#7,618,361
of 23,225,652 outputs
Outputs from arXiv
#171,070
of 957,260 outputs
Outputs of similar age
#164,245
of 457,349 outputs
Outputs of similar age from arXiv
#5,995
of 27,853 outputs
Altmetric has tracked 23,225,652 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 957,260 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 80% 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 457,349 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 56% of its contemporaries.
We're also able to compare this research output to 27,853 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.

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