A predictive machine learning application in agriculture: Cassava disease detection and classification with imbalanced dataset using convolutional neural networks
This work is inspired by Kaggle competition which was part of the Fine-Grained Visual Categorization workshop at CVPR 2019 (Conference on Computer Vision and Pattern Recognition) we participated in.It aimed at detecting cassava diseases the gel bottle audrey using 5 fine-grained cassava leaf disease categories with 10,000, labeled images collected