This article introduces an approach for soybean yield prediction by integrating convolutional long short-term memory (ConvLSTM), three-dimensional convolutional neural network (3D-CNN), and vision ...

Crop yield prediction focuses mostly on agricultural research, which have an enormous impact on taking decisions for example import-export, price, along with crop management. Accurate forecasting with ...

About This is a project on Crop yeld prediction using different algorithms and used a neural network at the ending to get more accurate results.

About Developed and implemented a sophisticated Artificial Neural Network (ANN) model to forecast crop yields, leveraging a comprehensive dataset of weather parameters and historical crop yields.

Flowchart of the experimental design for imaging, segmentation, fruit quality (oil and total phenols) determinations, and modeling through back propagation neural networks (BPNNs).

Real-time monitoring of crop growth has become indispensable in modern agriculture, facilitating prompt detection of crop stress, diseases, and nutrient deficiencies by farmers. This study ...

The researchers compared four forms of the neural network’s output to some of the more common yield prediction tools, including linear regression and a random forest algorithm. They found that the ...