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How we know universals the perception of auditory and visual forms
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Citations
Cited by
Object Detection With Deep Learning: A Review
Zhao, Z.-Q., Zheng, P., Xu, S.-T., & Wu, X. (2019) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2876865 · Cited by 5,545
What the frog's eye tells the frog's brain
Lettvin, J., Maturana, H., McCulloch, W., & Pitts, W. (1959) · Proceedings of the IRE · doi:10.1109/jrproc.1959.287207 · Cited by 1,990
Self-citationOlshausen, B., Anderson, C., & Van Essen, D. (1993) · The Journal of Neuroscience · doi:10.1523/jneurosci.13-11-04700.1993 · Cited by 908
Proxemics [and Comments and Replies]
Hall, E. T., Birdwhistell, R. L., Bock, B., Bohannan, P., Diebold, Durbin, M., Edmonson, M. S., Fischer, J. L., Hymes, D., Kimball, S. T., et al. (1968) · Current Anthropology · doi:10.1086/200975 · Cited by 678
Is perception discrete or continuous?
VanRullen, R., & Koch, C. (2003) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(03)00095-0 · Cited by 662
Dynamic Model of Visual Recognition Predicts Neural Response Properties in the Visual Cortex
Rao, R. P. N., & Ballard, D. H. (1997) · Neural Computation · doi:10.1162/neco.1997.9.4.721 · Cited by 290
The neurophysics of consciousness
John, E. R. (2002) · Brain Research Reviews · doi:10.1016/s0165-0173(02)00142-x · Cited by 262
Deep Reinforcement Learning for the Control of Robotic Manipulation: A Focussed Mini-Review
Liu, R., Nageotte, F., Zanne, P., de Mathelin, M., & Dresp-Langley, B. (2021) · Robotics · doi:10.3390/robotics10010022 · Cited by 188
Interactive Activation and Mutual Constraint Satisfaction in Perception and Cognition
McClelland, J. L., Mirman, D., Bolger, D. J., & Khaitan, P. (2014) · Cognitive Science · doi:10.1111/cogs.12146 · Cited by 122
Autonomous marine robot based on AI recognition for permanent surveillance in marine protected areas
Molina-Molina, J. C., Salhaoui, M., Guerrero-González, A., & Arioua, M. (2021) · Sensors · doi:10.3390/s21082664 · Cited by 48
University of Messina, M., Damiano, L., Stano, P., & University of Salento, L. (2018) · Complex Systems · doi:10.25088/complexsystems.27.3.199 · Cited by 28
Ceruti, M., & Damiano, L. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.02204 · Cited by 8
Damiano, L., Fleres, A., Roli, A., & Stano, P. (2026) · Frontiers in Robotics and AI · doi:10.3389/frobt.2025.1694338 · Cited by 2
“Yet, importantly, based on their recognition of the oversimplifications embedded in the 1943 model, McCulloch and Pitts presented a markedly different and more biologically plausible framework in their 1947 paper “How We Know Universals” (Pitts and McCulloch, 1947).”
Metadata
- Authors
- Pitts, W., & McCulloch, W. S.
- Venue
- The Bulletin of Mathematical Biophysics
- Published
- 1947-09
- Volume
- 9
- Issue
- 3
- Pages
- 127-147
- ISSN
- 0092-8240 (ISSN-L)
- 0007-4985
- 1522-9602
- OpenAlex
- W118296737
- Cited by
- 799
- References
- 0
- FWCI
- 9.52
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
