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Por favor, use este identificador para citar o enlazar este ítem: https://repositorio.uide.edu.ec/handle/37000/7981
Título : Maturity Classification of Pitahaya Fruit Based on Deep Learning
Autor : Ortiz Santander, Alexis David
Pilco Ati, Andrea Estefanía (tutor)
Palabras clave : MATURITY CLASSIFICATION;PITAHAYA;DEEP LEARNING;MECATRÓNICA
Fecha de publicación : 2025
Editorial : QUITO/UIDE/2025
Citación : Ortiz Santander, Alexis David. (2025). Maturity Classification of Pitahaya Fruit Based on Deep Learning. Facultad de Mecatrónica. UIDE. Quito. 41 p.
Resumen : Agriculture has long been a cornerstone of human development, providing not only sus tenance but also driving economic growth and societal well-being [1]. However, the rapid rise in global consumption driven by population growth presents significant challenges for agricultural production [2]. These challenges necessitate the adoption of advanced tech nologies to enhance both production and sustainability [3]. Among these challenges, the accurate classification of fruit maturity stands out as a critical area. Proper classification enables farmers to make informed decisions about harvesting and transportation, ensuring the quality and marketability of their produce. Yellow pitahaya (Selenicereus megalan thus), a tropical and subtropical horticultural crop, has garnered significant attention due to its unique appearance, taste, and high nutritional value.
URI : https://repositorio.uide.edu.ec/handle/37000/7981
Aparece en las colecciones: Tesis - Ingeniería en Mecatrónica

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