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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21508
Article Published : 8513
Total Authors : 22399
Total Reviewer : 805
Total Countries : 158
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Published Paper Details
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| Paper Title: | Plant Leaf Disease Detection using Computer Vision Techniques and Machine Learning |
| Authors Name: | P.Pandi selvi , A.Goro John |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_186199
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| Published Paper Id: | IJRTI2304239 |
| Published In: | Volume 8 Issue 4, April-2023 |
| DOI: | |
| Abstract: | Agriculture plays a vital role in the economy of the country. It is the main source of food to sustain on earth. It needs to be preserved. In recent days there were some downfall in the field of agriculture, due to variuos reasons as rainfall, flood, fertilizers, diseases in plants and various other reasons. Hence in order to improve the productivity and economy of the country, it is necessary to predict the diseases in plants at an early stage. Early detection of disease in plants is critical in the field of agriculture. The automatic disease detection at an early-stage is helpful as it decreases the great effort of supervising in large farmhouses of yields. Using digital image processing techniques and machine learning algorithms, the authors presented a method for detecting plant diseases at an early stage. The presented system for plant disease detection is simple and computationally efficient which requires less time for prediction than other deep learning-based approaches. The accuracies of various plant and leaf diseases are calculated and presented in this paper. |
| Keywords: | Machine learning algorithms, CNN. |
| Cite Article: | "Plant Leaf Disease Detection using Computer Vision Techniques and Machine Learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 4, page no.1458 - 1461, April-2023, Available :http://www.ijrti.org/papers/IJRTI2304239.pdf |
| Downloads: | 000205373 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2304239
Registration ID:186199
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 1458 - 1461 Country: Madurai, Tamilnadu, India Research Area: Science Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2304239 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2304239 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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