The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A machine learning approach for automated recognition of movement patterns using basic, kinetic and kinematic gait data
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Citations
Cites
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
Lord, S. R., Castell, S., Corcoran, J., Dayhew, J., Matters, B., Shan, A., & Williams, P. (2003) · Journal of the American Geriatrics Society · doi:10.1046/j.1532-5415.2003.51551.x · Cited by 416
Cited by
Human model evaluation in interactive supervised learning
Fiebrink, R., Cook, P. R., & Trueman, D. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1978965 · Cited by 207
Lau, H.-Y., Tong, K.-Y., & Zhu, H. (2009) · Human Movement Science · doi:10.1016/j.humov.2008.12.003 · Cited by 108
Fong, J., Ocampo, R., Gross, D. P., & Tavakoli, M. (2020) · Journal of Occupational Rehabilitation · doi:10.1007/s10926-020-09888-w · Cited by 52
Prediction of gait trajectories based on the Long Short Term Memory neural networks
Zaroug, A., Garofolini, A., Lai, D. T. H., Mudie, K., & Begg, R. (2021) · PLOS ONE · doi:10.1371/journal.pone.0255597 · Cited by 48
Self-citationDaily Locomotion Recognition and Prediction: A Kinematic Data-Based Machine Learning Approach
Figueiredo, J., Carvalho, S. P., Goncalve, D., Moreno, J. C., & Santos, C. P. (2020) · IEEE Access · doi:10.1109/access.2020.2971552 · Cited by 37
Metadata
- Authors
- Begg, R., & Kamruzzaman, J.
- Venue
- Journal of Biomechanics
- Publisher
- Elsevier BV
- Published
- 2005-03
- Volume
- 38
- Issue
- 3
- Pages
- 401-408
- ISSN
- 0021-9290 (ISSN-L)
- OpenAlex
- W2080718748
- Cited by
- 326
- References
- 2
- FWCI
- 5.30
- 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.
Statistics and arithmetic are recomputed, not judged.
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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.
