TITLE:
Detection of “Swollen Shoot” Disease in Ivorian Cocoa Trees via Convolutional Neural Networks
AUTHORS:
Mamadou Coulibaly, Konan Hyacinthe Kouassi, Silue Kolo, Olivier Asseu
KEYWORDS:
Drone, Convolutional Neural Networks, Image Recognition, Feature Detection
JOURNAL NAME:
Engineering,
Vol.12 No.3,
March
12,
2020
ABSTRACT: Recent advances in diagnostics have made image analysis one of the main areas of research and development. Selecting and calculating these characteristics of a disease is a difficult task. Among deep learning techniques, deep convolutional neural networks are actively used for image analysis. This includes areas of application such as segmentation, anomaly detection, disease classification, computer-aided diagnosis. The objective which we aim in this article is to extract information in an effective way for a better diagnosis of the plants attending the disease of “swollen shoot”.