OlivesApp: Aplicativo de Classificação do Índice de Maturação de Azeitonas através do YOLOv8

This work presents the development of an application designed to detect and classify the ripeness index of olives using YOLOv8. The main objective is to provide a practical and accessible solution for olive growers and researchers, facilitating analysis and decision-making related to olive harvesting and cultivation. The application employs image processing algorithms to identify specific characteristics of olives in digital images, classifying their ripeness quickly and efficiently. The results indicate that the application has great potential to optimize production processes and improve the quality of olives and olive oil.

Authors

Institutions

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.5753/webmedia_estendido.2024.244038
Primary Topic
Agricultural and Food Sciences
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

OlivesApp: Aplicativo de Classificação do Índice de Maturação de Azeitonas através do YOLOv8

Cleiton Antônio Nunes, Amanda Carolina Souza Andrada Anconi, Everaldo B. Alves, Diogo da Silva Alvino et al.
1 links
Agricultural and Food Sciences
article

OlivesApp: Aplicativo de Classificação do Índice de Maturação de Azeitonas através do YOLOv8

Cleiton Antônio Nunes, Amanda Carolina Souza Andrada Anconi, Everaldo B. Alves, Diogo da Silva Alvino, Jhon Randler dos Santos Belarmino, Warley M. Valente, Aline Santana Oliveira Valente
article en

Abstract

This work presents the development of an application designed to detect and classify the ripeness index of olives using YOLOv8. The main objective is to provide a practical and accessible solution for olive growers and researchers, facilitating analysis and decision-making related to olive harvesting and cultivation. The application employs image processing algorithms to identify specific characteristics of olives in digital images, classifying their ripeness quickly and efficiently. The results indicate that the application has great potential to optimize production processes and improve the quality of olives and olive oil.

Universidade Federal do Sul e Sudeste do Pará (BR)
Openalex Percentile: Top 76%
Agricultural and Food Sciences
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.