TY  - JOUR 
AU  - Zanella, Marco Antonio
AU  - Barrio-Conde, Mikel
AU  - Gomez-Gil, Jaime
AU  - Aguiar-Perez, Javier Manuel
AU  - Pérez-Juárez, María Ángeles
AU  - da Silva, Pablo Moreira
PY  - 2025
SN  - 1678-992X
UR  - https://uvadoc.uva.es/handle/10324/83819
AB  - The coffee industry is a vital sector of global agriculture. Coffee is one of the most widely traded plant products in the world. Coffee fruit ripeness affects the taste and aroma of the final brewed beverage, coffee farms’ overall yield and economic...
LA  - eng
PB  - ScIELO
KW  - Agricultura de precisión
KW  - Machine learning
KW  - Aprendizaje automático
KW  - Sustainable agriculture
KW  - Agricultural innovations
KW  - Agricultura - Innovaciones tecnológicas
KW  - Neural networks (Computer science)
KW  - Computer vision
KW  - Visión artificial (Robótica)
KW  - Agricultural engineering
KW  - Agriculture
KW  - YOLO
KW  - coffee farming
KW  - fruit detection
KW  - precision agriculture
TI  - Deep learning to classify the ripeness of coffee fruit in the mechanized harvesting process
DO  - https://doi.org/10.1590/1678-992X-2024-0156
ER  -