An analytical Survey on Predicting Crop Yield through Deep Learning techniques

Computer Engineering

Agricultural production is one of the most essential ethical considerations just because it produces a large amount of food. Currently, hundreds of countries are nevertheless starved as a result of food scarcity or a scarcity of supplies with an expanding economy. A country's prosperity is heavily reliant on agricultural products and the productivity of crops grown in that location. The dependency on agriculture has been critical for a nation's prosperity and progress, since a well-fed and fit and active population has a far stronger immune system and success than a community with subpar nutrition and health supply. Asia is primarily an agricultural economy, with farming accounting for a substantial portion of its trade. The agricultural process is a complicated activity that does not allow for exact prediction of crop production. Without proper production projections, the farmer cannot plan efficiently, that might also result in unanticipated damages. As a result, there is a demand for an effective technique for predicting agricultural yields using machine learning techniques. This literature survey study summarized and examined an effective collection of studies to reach our strategy, which will be detailed in the future research article on this issue.

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