Insect damage assessment of tropical grasses under field conditions using a modular pipeline with image processing and deep learning techniques

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dc.creatorRuiz-Hurtado, Andres Felipe
dc.creatorEspitia Buitrago, Paula
dc.creatorKimani, Adrian Mating'l
dc.creatorChidawanyika, Frank
dc.creatorCardoso, Juan
dc.creatorJauregui, Rosa N
dc.date2024-10-07
dc.date2024-11-13T12:05:39Z
dc.date2024-11-13T12:05:39Z
dc.date.accessioned2026-06-27T13:37:36Z
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/159652
dc.identifier.urihttp://hdl.handle.net/123456789/65296
dc.languageen
dc.rightsOpen Access
dc.sourceRuiz-Hurtado, A.F.; Espitia Buitrago, P.; Kimani, A.M.; Chidawanyika, F.; Cardoso, J.; Jauregui, R.N. (2024) Insect damage assessment of tropical grasses under field conditions using a modular pipeline with image processing and deep learning techniques. Poster Prepared for the 8th International Plant Phenotyping Symposium on 7-11 October 2024 in Nebraska (USA). 1 p.
dc.subjectproductivity
dc.subjectphenotyping
dc.subjectfenotipado
dc.subjectinsect diseases
dc.subjectproductividad
dc.subjectimage processing
dc.subjectprocesamiento digital de imágenes
dc.subjecttolerance to pests
dc.subjectinsecto
dc.subjecttolerancia a enfermedades
dc.titleInsect damage assessment of tropical grasses under field conditions using a modular pipeline with image processing and deep learning techniques
dc.typePoster

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