Viziometrics: Analyzing Visual Information in the Scientific Literature

@article{Lee2018ViziometricsAV,
  title={Viziometrics: Analyzing Visual Information in the Scientific Literature},
  author={Po-Shen Lee and J. West and B. Howe},
  journal={IEEE Transactions on Big Data},
  year={2018},
  volume={4},
  pages={117-129}
}
  • Po-Shen Lee, J. West, B. Howe
  • Published 2018
  • Computer Science
  • IEEE Transactions on Big Data
  • Scientific results are communicated visually in the literature through diagrams, visualizations, and photographs. These information-dense objects have been largely ignored in bibliometrics and scientometrics studies when compared to citations and text. In this paper, we use techniques from computer vision and machine learning to classify more than 8 million figures from PubMed into five figure types and study the resulting patterns of visual information as they relate to scholarly impact. We… CONTINUE READING
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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 47 REFERENCES
    On-line adaptive background modelling for audio surveillance
    23
    Respiratory syncytial virus, p. 1313–1351
    • 1996
    ApJ
    • 1996
    Electromechanical transducers and wave filters
    605