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  Published Paper Details:

  Paper Title

Weed Detection In Crops Using Convolutional Neural Networks

  Authors

  K.Tejashwini,  M.Soumya,  P.Kalyani,  Dr.C.N.Sujatha,  Mrs.G.Deepika

  Keywords

CNN, colour segmentation, agriculture, and image processing.

  Abstract


Agriculture was one of the first methods used by humans to survive on our planet.. Today, in order to fulfil demand, we need agriculture to be more productive. This is due to the expanding population. In the past, humans increased output naturally by utilising things like cow dung as a fertiliser for the fields. This led to an increase in output sufficient to meet the population's needs. But with time, people started to think about boosting profits by having more success. Consequently, the "Green Revolution"--a revolution--began. Herbicides and other deadly poisons were then used far more frequently. While doing so, we increased productivity but neglected to take into account the environmental damage that was incurred, raising concerns about our ability to exist on this beautiful world. To reduce the usage of herbicides by only using them where weeds are present, we have implemented many solutions in this research. With this research, we use MATLAB to develop image processing to identify weed regions in an image we captured in the fields. Precision agriculture is gaining more and more attention from experts Since the global population has increased recently and the amount of available land and natural resources has reduced techniques for image processing could be used to address this issue.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2308144

  Paper ID - 241782

  Page Number(s) - b277-b286

  Pubished in - Volume 11 | Issue 8 | August 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  K.Tejashwini,  M.Soumya,  P.Kalyani,  Dr.C.N.Sujatha,  Mrs.G.Deepika,   "Weed Detection In Crops Using Convolutional Neural Networks", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 8, pp.b277-b286, August 2023, Available at :http://www.ijcrt.org/papers/IJCRT2308144.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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