Agricultural Information System Using Machine Learning

Authors

  • B. Kavitha   Lecturer, Department of Computer Engineering, IRT polytechnic college, Chennai, India

Keywords:

ANN, CNN, Machine Learning, Pattern Recognition

Abstract

Artificial intelligence includes machine learning as a subfield. A lot of academic and industrial circles have been concerned about it recently because of the benefits of autonomous learning and feature extraction. Processing of images and videos, audio, and natural language has all made extensive use of it. A research hotspot for agricultural plant protection, including the identification of plant diseases and the evaluation of pest ranges, has also emerged at the same time. Plant disease feature extraction can become more objective through the use of machine learning, which can also reduce the drawbacks associated with artificial selection of disease spot features. Additionally, machine learning can speed up technological transformation and increase search efficiency. Plant disease detection, crop growth forecasts for the field, and fertilizer recommendations are all included in the proposed work.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-06-30

Issue

Volume 4, Issue 9, July-August-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
B. Kavitha "Agricultural Information System Using Machine Learning" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 9, pp.693-697, July-August-2018.