Detección de enfermedades de las hojas de las plantas utilizando avances recientes en técnicas de identificación basadas en aprendizaje profundo
Resumen
En su mayor parte, la economía depende profundamente de la eficiencia agrícola. Los cultivos agrícolas se ven comúnmente afectados por la enfermedad. Dado que la economía depende de la agricultura, esta es una de las razones principales por las que la identificación de infecciones en las plantas asume un trabajo importante en el campo de la horticultura. En el caso de que no se tome una consideración legítima aquí, en ese momento, esto causa consecuencias naturales para las plantas y por qué la calidad, cantidad o eficiencia del artículo en particular influye. La mala suerte de los cultivos debido a enfermedades influye considerablemente en la economía y socava la accesibilidad a los alimentos. La ubicación rápida y precisa de las enfermedades de las plantas es esencial para expandir la eficiencia agrícola de manera sustentable. En cualquier caso, la ubicación de la planta por parte de especialistas humanos es costosa, tediosa y, a veces, poco realista. Para contrarrestar estas dificultades, los fitopatólogos quieren un marco de conclusión de enfermedades de las plantas exacto y confiable. La utilización continua del procedimiento de aprendizaje profundo con métodos de procesamiento de imágenes para el reconocimiento de enfermedades de las plantas se ha convertido en un tema de examen candente para realizar un análisis programado. Esta investigación proporciona una técnica de prueba de diferenciación de enfermedades de plantas productivas que depende de modelos de aprendizaje profundo preparados previamente, como los diseños de AlexNet y GoogleNet. Confiamos en que este trabajo será un activo importante para los analistas en el área de reconocimiento de dolencias que utilizan estrategias de manejo de imágenes con arquitecturas de aprendizaje profundo.
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