The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
Plant disease detection using computational intelligence and image processing
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Citations
Cites
Going deeper with convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298594 · Cited by 48,562
Object recognition from local scale-invariant features
Lowe, D. G. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.790410 · Cited by 16,472 · cited 1×
“SIFT is the feature descriptor which represents local features of images in feature vectors; each feature is invariant to scale transformation (Lowe 1999).”
BackgroundA comparative study of texture measures with classification based on featured distributions
Ojala, T., Pietikäinen, M., & Harwood, D. (1996) · Pattern Recognition · doi:10.1016/0031-3203(95)00067-4 · Cited by 6,882
Габор, Д. (1946) · Journal of the IEE · Cited by 5,036
Using Deep Learning for Image-Based Plant Disease Detection
Mohanty, S. P., Hughes, D. P., & Salathé, M. (2016) · Frontiers in Plant Science · doi:10.3389/fpls.2016.01419 · Cited by 5,026
Deep learning models for plant disease detection and diagnosis
Ferentinos, K. P. (2018) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2018.01.009 · Cited by 3,390
Zur Theorie der orthogonalen Funktionensysteme: Erste Mitteilung
Haar, A. (1910) · Mathematische Annalen · doi:10.1007/bf01456326 · Cited by 2,138
Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification
Sladojevic, S., Arsenovic, M., Anderla, A., Culibrk, D., & Stefanovic, D. (2016) · Computational Intelligence and Neuroscience · doi:10.1155/2016/3289801 · Cited by 2,029
Theory of communication. Part 1: The analysis of information
Gabor, D. (1946) · Journal of the Institution of Electrical Engineers - Part III: Radio and Communication Engineering · doi:10.1049/ji-3-2.1946.0074 · Cited by 1,795
A Robust Deep-Learning-Based Detector for Real-Time Tomato Plant Diseases and Pests Recognition
Fuentes, A., Yoon, S., Kim, S., & Park, D. (2017) · Sensors · doi:10.3390/s17092022 · Cited by 1,572
Cited by
Diagnosis of grape leaf diseases using automatic K-means clustering and machine learning
Javidan, S. M., Banakar, A., Vakilian, K. A., & Ampatzidis, Y. (2023) · Smart Agricultural Technology · doi:10.1016/j.atech.2022.100081 · Cited by 258
Metadata
- Authors
- Vishnoi, V. K., Kumar, K., & Kumar, B.
- Venue
- Journal of Plant Diseases and Protection
- Published
- 2020-08-30
- Volume
- 128
- Issue
- 1
- Pages
- 19-53
- ISSN
- 1861-3829 (ISSN-L)
- 1861-3837
- OpenAlex
- W3082480853
- Cited by
- 308
- References
- 71
- FWCI
- 20.96
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Vishnoi, V. K., Kumar, K., & Kumar, B. (2021). Plant disease detection using computational intelligence and image processing. Journal of Plant Diseases and Protection. https://doi.org/10.1007/s41348-020-00368-0
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.
