IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v64y2014icp48-66.html
   My bibliography  Save this article

Pattern recognition at different scales: A statistical perspective

Author

Listed:
  • Colangeli, Matteo
  • Rugiano, Francesco
  • Pasero, Eros

Abstract

In this paper we borrow concepts from Information Theory and Statistical Mechanics to perform a pattern recognition procedure on a set of X-ray hazelnut images. We identify two relevant statistical scales, whose ratio affects the performance of a machine learning algorithm based on statistical observables, and discuss the dependence of such scales on the image resolution. Finally, by averaging the performance of a Support Vector Machines algorithm over a set of training samples, we numerically verify the predicted onset of an “optimal” scale of resolution, at which the pattern recognition is favoured.

Suggested Citation

  • Colangeli, Matteo & Rugiano, Francesco & Pasero, Eros, 2014. "Pattern recognition at different scales: A statistical perspective," Chaos, Solitons & Fractals, Elsevier, vol. 64(C), pages 48-66.
    • Handle: RePEc:eee:chsofr:v:64:y:2014:i:c:p:48-66
    DOI: 10.1016/j.chaos.2013.10.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077913001963
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2013.10.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Anne Condon, 2011. "DNA and the brain," Nature, Nature, vol. 475(7356), pages 304-305, July.
    2. Lulu Qian & Erik Winfree & Jehoshua Bruck, 2011. "Neural network computation with DNA strand displacement cascades," Nature, Nature, vol. 475(7356), pages 368-372, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lahmiri, Salim, 2016. "Image characterization by fractal descriptors in variational mode decomposition domain: Application to brain magnetic resonance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 235-243.
    2. Ancillao, Andrea & Galli, Manuela & Rigoldi, Chiara & Albertini, Giorgio, 2014. "Linear correlation between fractal dimension of surface EMG signal from Rectus Femoris and height of vertical jump," Chaos, Solitons & Fractals, Elsevier, vol. 66(C), pages 120-126.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Avik Samanta & Maximilian Hörner & Wei Liu & Wilfried Weber & Andreas Walther, 2022. "Signal-processing and adaptive prototissue formation in metabolic DNA protocells," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Linlin Yang & Qian Tang & Mingzhi Zhang & Yuan Tian & Xiaoxing Chen & Rui Xu & Qian Ma & Pei Guo & Chao Zhang & Da Han, 2024. "A spatially localized DNA linear classifier for cancer diagnosis," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    3. Tai-Yin Chiu & Hui-Ju K Chiang & Ruei-Yang Huang & Jie-Hong R Jiang & François Fages, 2015. "Synthesizing Configurable Biochemical Implementation of Linear Systems from Their Transfer Function Specifications," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-27, September.
    4. Ferdinand Greiss & Nicolas Lardon & Leonie Schütz & Yoav Barak & Shirley S. Daube & Elmar Weinhold & Vincent Noireaux & Roy Bar-Ziv, 2024. "A genetic circuit on a single DNA molecule as an autonomous dissipative nanodevice," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    5. Kanakov, Oleg & Chen, Shangbin & Zaikin, Alexey, 2024. "Learning by selective plasmid loss for intracellular synthetic classifiers," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    6. Hong Kang & Yuexuan Yang & Bryan Wei, 2024. "Synthetic molecular switches driven by DNA-modifying enzymes," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    7. Ahmed A. Agiza & Kady Oakley & Jacob K. Rosenstein & Brenda M. Rubenstein & Eunsuk Kim & Marc Riedel & Sherief Reda, 2023. "Digital circuits and neural networks based on acid-base chemistry implemented by robotic fluid handling," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    8. Luna Rizik & Loai Danial & Mouna Habib & Ron Weiss & Ramez Daniel, 2022. "Synthetic neuromorphic computing in living cells," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    9. Russell Bates & Oleg Blyuss & Ahmed Alsaedi & Alexey Zaikin, 2015. "Effect of Noise in Intelligent Cellular Decision Making," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-16, May.
    10. Karen Zhang & Yuan-Jyue Chen & Delaney Wilde & Kathryn Doroschak & Karin Strauss & Luis Ceze & Georg Seelig & Jeff Nivala, 2022. "A nanopore interface for higher bandwidth DNA computing," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    11. Betz, Ulrich A.K. & Arora, Loukik & Assal, Reem A. & Azevedo, Hatylas & Baldwin, Jeremy & Becker, Michael S. & Bostock, Stefan & Cheng, Vinton & Egle, Tobias & Ferrari, Nicola & Schneider-Futschik, El, 2023. "Game changers in science and technology - now and beyond," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    12. Jianbang Wang & Zhenzhen Li & Itamar Willner, 2022. "Cascaded dissipative DNAzyme-driven layered networks guide transient replication of coded-strands as gene models," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:64:y:2014:i:c:p:48-66. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.