Autor:
Ramcharan, A.
McCloskey, P.
Baranowski, K.
Mbilinyi, N.
Mrisho, L.
Ndalahwa, M.
Legg, J.P.
Hughes, D.P.
Convolutional neural network (CNN) models have the potential to improve plant disease phenotyping where the standard approach is visual diagnostics requiring specialized training. In scenarios where a CNN is deployed on mobile devices, models are presented with new challenges due to lighting and ...
Enlace original:
https://cgspace.cgiar.org/handle/10568/105535
Ramcharan, A.
,
McCloskey, P.
,
Baranowski, K.
,
Mbilinyi, N.
,
Mrisho, L.
,
Ndalahwa, M.
,
Legg, J.P.
,
Hughes, D.P.
,
[A mobile-based deep learning model for cassava disease diagnosis]
,
A mobile-based deep learning model for cassava disease diagnosis
