About this document
Deep Learning for Cabbage Seedling Prediction by Raddan Agimular is a document available to read on EtoBox.
This document presents a study that uses convolutional neural networks to classify images of white cabbage seedlings and predict their successful growth. The study uses a dataset of 13,200 seedling images taken over 14 days from a controlled environment. Different neural network models are tested, including AlexNet, and are found to outperform traditional statistical methods like logistic regression. Specifically, AlexNet accurately classifies 94% of seedlings and can be useful as an early warning tool for
- Author
- Raddan Agimular
- Language
- EN