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- W4319778051 abstract "The infections and the spread of plant diseases in various crops is a matter of concern as agriculture is a promising sector that contributes to nation’s economy. The diseases affecting the crops are the main cause of low yield. The detection of plant diseases in initial stage will help agricultural producers to have better yield. The imports of the crops and its form can considerably be reduced and help to feed the country’s population. Thus, strengthen the overall economic of the country. This study summarizes the work done using the current methods such as deep learning techniques, which are adopted for the diagnosis of different diseases especially in the oilseed segment of agriculture sector. This study provides the promising area of research, and will facilitate the researchers to look for opportunities in oilseed segment to give their contribution by developing models which make use of the deep learning technology like convolutional neural networks which will be low cost, reliable and effective." @default.
- W4319778051 created "2023-02-11" @default.
- W4319778051 creator A5051107367 @default.
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- W4319778051 date "2022-11-04" @default.
- W4319778051 modified "2023-10-18" @default.
- W4319778051 title "A Study of Deep Learning Techniques on Oilseed Crops" @default.
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- W4319778051 doi "https://doi.org/10.1109/icccis56430.2022.10037740" @default.
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