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Please use this identifier to cite or link to this item: https://repositorio.uide.edu.ec/handle/37000/7981
Title: Maturity Classification of Pitahaya Fruit Based on Deep Learning
Authors: Ortiz Santander, Alexis David
Pilco Ati, Andrea Estefanía (tutor)
Keywords: MATURITY CLASSIFICATION;PITAHAYA;DEEP LEARNING;MECATRÓNICA
Issue Date: 2025
Publisher: QUITO/UIDE/2025
Citation: Ortiz Santander, Alexis David. (2025). Maturity Classification of Pitahaya Fruit Based on Deep Learning. Facultad de Mecatrónica. UIDE. Quito. 41 p.
Abstract: 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
Appears in Collections:Tesis - Ingeniería en Mecatrónica

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