Assessing deep convolutional neural network models and their comparative performance for automated medicinal plant identification from leaf images.

ABSTRACT: Medicinal plants have got notable attention in recent years in the field of pharmaceutical and drug research. The high demand of herbal medicine in the rural areas of developing countries and drug industries necessitates correct identification of the medicinal plant species which is challenging in absence of expert taxonomic knowledge. Against this backdrop, we attempted to assess the performance of seven advanced deep learning algorithms in the automated identification of the plants from their leaf images and to suggest the best model from a comparative study of the models. We meticulously trained VGG16, VGG19, DenseNet201, ResNet50V2, Xception, InceptionResNetV2, and InceptionV3 deep neural network models. This training utilized a dataset comprising 5878 images encompassing 30 medicinal

SUBMITTER: Dey B 

PROVIDER: S-EPMC10767391 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature