Paper Title
Intelligent Recommendation System For Agricultural Cultivation
Article Identifiers
Authors
G. Sai Krishna , D. Calvin Antony , G. Siva Shankar
Keywords
Machine learning, CNN, ANN, Random Forest, RESNET
Abstract
When growing crops, farmers face a number of difficulties, including erratic irrigation, subpar soil, etc. A significant portion of farmers, particularly in India, lack the knowledge necessary to choose the right crops and fertilizers. Additionally, both farmers and consumers suffer significant losses when crops fail due to disease. The use of Deep Learning has not been adequately investigated, despite recent advancements in the automated identification of certain diseases utilizing Machine Learning approaches. Such models are also difficult to employ due to the good quality data used in their learning, a absence of processing capacity, and the algorithms' weak generalization capabilities. In order to do this, we develop an open-source, user-friendly online application to address some of these problems.
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How To Cite (APA)
G. Sai Krishna, D. Calvin Antony , & G. Siva Shankar (May-2023). Intelligent Recommendation System For Agricultural Cultivation. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), b41-b45. https://ijnrd.org/papers/IJNRD2305108.pdf
Issue
Volume 8 Issue 5, May-2023
Pages : b41-b45
Other Publication Details
Paper Reg. ID: IJNRD_194031
Published Paper Id: IJNRD2305108
Downloads: 000121985
Research Area: Engineering
Country: prakasam, Andhra Pradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2305108.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305108
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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