The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Natural Image Statistics
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Independent Component Analysis
(2004) · Independent Component Analysis · doi:10.7551/mitpress/3717.003.0014 · Cited by 7,903
Brown, L. R., Wolf, E. C., & Bell, R. E. (1996) · Cited by 928
Hinton, G. E. (1999) · 9th International Conference on Artificial Neural Networks: ICANN '99 · doi:10.1049/cp:19991075 · Cited by 341
Müller, J. (2009) · doi:10.1037/11919-047 · Cited by 144
Information transmission in the nervous system
Uttley, A. M. (1979) · Medical Entomology and Zoology · Cited by 41
Lateral Interactions and Feedback
Hyvärinen, A., Hurri, J., & Hoyer, P. O. (2009) · Computational imaging and vision · doi:10.1007/978-1-84882-491-1_14 · Cited by 1
Self-citationSayood, K. (2021) · Synthesis lectures on signal processing · doi:10.1007/978-3-031-02545-7_18 · Cited by 1
Cited by
Representation Learning: A Review and New Perspectives
Bengio, Y., Courville, A., & Vincent, P. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.50 · Cited by 13,001
Ali, S., Abuhmed, T., El-Sappagh, S., Muhammad, K., Alonso-Moral, J. M., Confalonieri, R., Guidotti, R., Del Ser, J., Díaz-Rodríguez, N., & Herrera, F. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.101805 · Cited by 1,762
Building high-level features using large scale unsupervised learning
Le, Q. V. (2013) · 2013 IEEE International Conference on Acoustics, Speech and Signal Processing · doi:10.1109/icassp.2013.6639343 · Cited by 1,695
Deep Hashing Network for Efficient Similarity Retrieval
Zhu, H., Long, M., Wang, J., & Cao, Y. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i1.10235 · Cited by 664
A review of Convolutional-Neural-Network-based action recognition
Yao, G., Lei, T., & Zhong, J. (2019) · Pattern Recognition Letters · doi:10.1016/j.patrec.2018.05.018 · Cited by 437
Metadata
- Authors
- Hyvärinen, A., Hurri, J., & Hoyer, P. O.
- Venue
- Computational Imaging and Vision
- Publisher
- Springer London
- Published
- 2009
- ISSN
- 1381-6446 (ISSN-L)
- OpenAlex
- W104847522
- Cited by
- 398
- References
- 7
- FWCI
- 12.80
- Type
- book
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Natural Image Statistics. https://app.cochat.ai/papers/10.1007/978-1-84882-491-1
- The paper
- Hyvärinen, A., Hurri, J., & Hoyer, P. O. (2009). Natural Image Statistics. Computational Imaging and Vision. https://doi.org/10.1007/978-1-84882-491-1
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
