Identification of plant diseases using convolutional neural networks
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2020/02/07
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Indian UGC (journal)
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Refrences22
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Citations34
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Sachin B. Jadhav ORCID (unauthenticated)
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Vishwanath R. Udupi
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Sanjay B. Patil
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Digital image processing techniques for detecting, quantifying and classifying plant diseases | SpringerPlus | 160 | 2013 | |
| Detection and Classification of Leaf Diseases using K-means-based Segmentation and Neural-networks-based Classification | Information Technology Journal | 100 | 2011 | |
| Deep learning models for plant disease detection and diagnosis | Computers and Electronics in Agriculture |
| 886 | 2018 |
| Tomato crop disease classification using pre-trained deep learning algorithm | Procedia Computer Science | 201 | 2018 | |
| Deep Learning for Tomato Diseases: Classification and Symptoms Visualization | Applied Artificial Intelligence |
| 328 | 2017 |
Refrences Analysis
The category
Agriculture: Plant culture 6
is the most frequently represented among the references in this article. It primarily includes studies from International Journal of Computers and Applications and SpringerPlus. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
Citations Analysis
The category
Science: Mathematics: Instruments and machines: Electronic computers. Computer science 8
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled REVIEW ON THE TECHNIQUES USED FOR IDENTIFICATION OF
DISEASED LEAVES and was published in 2020. The most recent citation comes from a 2024 study titled Crops Leaf Disease Recognition From Digital and RS Imaging Using Fusion of Multi Self-Attention RBNet Deep Architectures and Modified Dragonfly Optimization. This article reached its peak citation in 2022, with 11 citations. It has been cited in 26 different journals, 23% of which are open access. Among related journals, the International Journal of Information Technology cited this research the most, with 6 citations. The chart below illustrates the annual citation trends for this article.