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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 |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
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UIDE-Q-TMECA-2025-68.pdf | CONFIDENCIAL | 199.55 kB | Adobe PDF | Visualizar/Abrir |
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