I designed a very simple neural network which 1 input and 1 output layer and 5 hidden layers.(all of them were dense layers) The purpose of this was to demonstrate that neural networks could be used ...

Crop yield prediction is a crucial task in agricultural science, involving the classification of potential yield into various levels. This is vital for both farmers and policymakers. The features ...

This repository contains my code for the "Crop Yield Prediction Using Deep Neural Networks" paper authered by Saeed Khaki and Lizhi Wang. The network is a deep feedforward neural network which uses ...

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 ...

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 ...

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