The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Automatic detection of ‘yellow rust’ in wheat using reflectance measurements and neural networks
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Citations
Cites
Neural networks for pattern recognition
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Learning Internal Representations by Error Propagation
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1985) · doi:10.21236/ada164453 · Cited by 16,172
Kohonen, T. (2001) · Springer Series in Information Sciences · doi:10.1007/978-3-642-56927-2 · Cited by 16,019
Klecka, W. (1980) · Sage eBooks · doi:10.4135/9781412983938 · Cited by 3,723
Parallel & distributed processing
Slusallek, P., Shirley, P., Mark, W., Stoll, G., & Wald, I. (2005) · ACM SIGGRAPH 2005 Courses on - SIGGRAPH '05 · doi:10.1145/1198555.1198750 · Cited by 2,568
Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation
Rouse, J. W. (1973) · NASA STI Repository (National Aeronautics and Space Administration) · Cited by 1,771
Neural Networks: A Pattern Recognition Perspective
Bishop, C. (1996) · Handbook of Neural Computation · doi:10.1201/9781420050646.ptb6 · Cited by 1,596
The decimal code for the growth stages of cereals, with illustrations
TOTTMAN, D. R. (1987) · Annals of Applied Biology · doi:10.1111/j.1744-7348.1987.tb03275.x · Cited by 660
Kohonen's Self Organizing Feature Maps for Exploratory Data Analysis
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Greenfield, A. A., Enslein, K., Ralston, A., & Wilf, H. S. (1978) · Applied Statistics · doi:10.2307/2346235 · Cited by 215
Cited by
Machine Learning in Agriculture: A Review
Liakos, K., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018) · Sensors · doi:10.3390/s18082674 · Cited by 3,441
Self-citationMahlein, A.-K. (2016) · Plant Disease · doi:10.1094/pdis-03-15-0340-fe · Cited by 1,363
Advanced methods of plant disease detection. A review
Martinelli, F., Scalenghe, R., Davino, S., Panno, S., Scuderi, G., Ruisi, P., Villa, P., Stroppiana, D., Boschetti, M., Goulart, L. R., et al. (2015) · Agronomy for Sustainable Development · doi:10.1007/s13593-014-0246-1 · Cited by 964
Lowe, A., Harrison, N., & French, A. P. (2017) · Plant Methods · doi:10.1186/s13007-017-0233-z · Cited by 654
Monitoring plant diseases and pests through remote sensing technology: A review
Zhang, J., Huang, Y., Pu, R., Gonzalez-Moreno, P., Yuan, L., Wu, K., & Huang, W. (2019) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2019.104943 · Cited by 623
Metadata
- Authors
- Moshou, D., Bravo, C., West, J., Wahlen, S., McCartney, A., & Ramon, H.
- Venue
- Computers and Electronics in Agriculture
- Publisher
- Elsevier BV
- Published
- 2004-09
- Volume
- 44
- Issue
- 3
- Pages
- 173-188
- ISSN
- 0168-1699 (ISSN-L)
- OpenAlex
- W2028606616
- Cited by
- 332
- References
- 11
- FWCI
- 3.00
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Automatic detection of ‘yellow rust’ in wheat using reflectance measurements and neural networks. https://app.cochat.ai/papers/10.1016/j.compag.2004.04.003
- The paper
- Moshou, D., Bravo, C., West, J., Wahlen, S., McCartney, A., & Ramon, H. (2004). Automatic detection of ‘yellow rust’ in wheat using reflectance measurements and neural networks. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2004.04.003
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.
