Crop Disease Prediction using Deep Learning Techniques - A Review Article Swipe
Gargi Sharma
,
Gourav Shrivastava
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.14445/23488387/ijcse-v9i4p104
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.14445/23488387/ijcse-v9i4p104
In agriculture, AI is bringing about a revolution by replacing traditional methods with more efficient ones and contributing to a better world. Artificial Intelligence and machine learning enable the development and implementation of devices that can identify and control plants, weeds, pests, and diseases through remote sensing. Plant disease lowers the quantity and quality of food, fiber, and biofuel crops, important to the Indian economy. In addition to reducing waste, using Deep learning technologies can increase quality and speed up market access for farmers. Here, we summarize recent crop disease detection research papers. Multiple deep learning algorithms demonstrate the current solutions for different crop disease diagnoses in this research. I hope this report will be useful to other crop disease detection researchers.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.14445/23488387/ijcse-v9i4p104
- https://www.internationaljournalssrg.org/../IJCSE/2022/Volume9-Issue4/IJCSE-V9I4P104.pdf
- OA Status
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- Cited By
- 10
- References
- 24
- Related Works
- 10
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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- DOI
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https://doi.org/10.14445/23488387/ijcse-v9i4p104Digital Object Identifier
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Crop Disease Prediction using Deep Learning Techniques - A ReviewWork title
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reviewOpenAlex work type
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enPrimary language
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2022Year of publication
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2022-04-25Full publication date if available
- Authors
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Gargi Sharma, Gourav ShrivastavaList of authors in order
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https://doi.org/10.14445/23488387/ijcse-v9i4p104Publisher landing page
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https://www.internationaljournalssrg.org/../IJCSE/2022/Volume9-Issue4/IJCSE-V9I4P104.pdfDirect link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://www.internationaljournalssrg.org/../IJCSE/2022/Volume9-Issue4/IJCSE-V9I4P104.pdfDirect OA link when available
- Concepts
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Deep learning, Agricultural engineering, Agriculture, Artificial intelligence, Crop, Quality (philosophy), Computer science, Biotechnology, Machine learning, Engineering, Agronomy, Geography, Biology, Philosophy, Archaeology, EpistemologyTop concepts (fields/topics) attached by OpenAlex
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10Total citation count in OpenAlex
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2025: 1, 2023: 9Per-year citation counts (last 5 years)
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24Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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