Convolutional Neural Network for the Detection of Cocoa Maturity with an Approach for the Analysis of Images Captured at Different Distances

Incorporating maturity assessment in the cocoa industry with neural networks. This project focuses on developing a convolutional neural network that accurately and efficiently identifies the degree of maturity of cocoa fruits. Divided into four increments, each addresses specific aspects of detection and classification, capturing images at different distances for a comprehensive approach. Contributing to improving the quality and efficiency of the cocoa harvest, promoting the application.