The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Generalization in vision and motor control
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Citations
Cites
Wu, Y. (1999) · Technometrics · doi:10.1080/00401706.1999.10485951 · Cited by 27,221
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Handbook of Sensory Physiology
Sanders, M. D. (1975) · British Journal of Ophthalmology · doi:10.1136/bjo.59.2.111-c · Cited by 7,166
Emergence of simple-cell receptive field properties by learning a sparse code for natural images
Olshausen, B. A., & Field, D. J. (1996) · Nature · doi:10.1038/381607a0 · Cited by 5,694
Hierarchical models of object recognition in cortex
Riesenhuber, M., & Poggio, T. (1999) · Nature Neuroscience · doi:10.1038/14819 · Cited by 3,309
Self-citationAdaptive representation of dynamics during learning of a motor task
Shadmehr, R., & Mussa-Ivaldi, F. (1994) · The Journal of Neuroscience · doi:10.1523/jneurosci.14-05-03208.1994 · Cited by 2,612
RECEPTIVE FIELDS AND FUNCTIONAL ARCHITECTURE IN TWO NONSTRIATE VISUAL AREAS (18 AND 19) OF THE CAT
Hubel, D. H., & Wiesel, T. N. (1965) · Journal of Neurophysiology · doi:10.1152/jn.1965.28.2.229 · Cited by 2,603
MODALITY AND TOPOGRAPHIC PROPERTIES OF SINGLE NEURONS OF CAT'S SOMATIC SENSORY CORTEX
Mountcastle, V. B. (1957) · Journal of Neurophysiology · doi:10.1152/jn.1957.20.4.408 · Cited by 2,400
Georgopoulos, A., Kalaska, J., Caminiti, R., & Massey, J. (1982) · The Journal of Neuroscience · doi:10.1523/jneurosci.02-11-01527.1982 · Cited by 2,130
Cited by
Robust Object Recognition with Cortex-Like Mechanisms
Serre, T., Wolf, L., Bileschi, S., Riesenhuber, M., & Poggio, T. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.56 · Cited by 1,667
Self-citationFast Readout of Object Identity from Macaque Inferior Temporal Cortex
Hung, C. P., Kreiman, G., Poggio, T., & DiCarlo, J. J. (2005) · Science · doi:10.1126/science.1117593 · Cited by 854
Self-citationMirror neurons: from origin to function
Cook, R., Bird, G., Catmur, C., Press, C., & Heyes, C. (2014) · Behavioral and Brain Sciences · doi:10.1017/s0140525x13000903 · Cited by 647
Miyawaki, Y., Uchida, H., Yamashita, O., Sato, M.-A., Morito, Y., Tanabe, H. C., Sadato, N., & Kamitani, Y. (2008) · Neuron · doi:10.1016/j.neuron.2008.11.004 · Cited by 543
Motor primitives in vertebrates and invertebrates
Flash, T., & Hochner, B. (2005) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2005.10.011 · Cited by 508
Metadata
- Authors
- Poggio, T., & Bizzi, E.
- Venue
- Nature
- Published
- 2004-10
- Volume
- 431
- Issue
- 7010
- Pages
- 768-774
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2028031284
- Cited by
- 386
- References
- 66
- FWCI
- 9.60
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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- CoChat. (2026). Citation check: Generalization in vision and motor control. https://app.cochat.ai/papers/10.1038/nature03014
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- Poggio, T., & Bizzi, E. (2004). Generalization in vision and motor control. Nature. https://doi.org/10.1038/nature03014
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.