Deep Learning based Medicinal Plants Leaf Recognition

Abstract

Plants assume a significant part in Earth’s nature by giving food, cover and keeping a solid environment.These plants contain some significant therapeutic qualities. Due to having fewer negative side effects and being more affordable than contemporary medicine, medicinal plants are receiving interest in the pharmaceutical business.In this work, I tried to classify the plant’s images through classical methods and Deep neural network.30 medicinal plants leaves are represented by 1835 images in the proposed dataset.First, I applied CNN to classify the images and got 65.66% ac curacy.Then I applied SVM with Normal features, GrayScale features, HOG fea tures and combined features extraction and got 72.28% accuracy for Normal fea tures,73.91% accuracy for GrayScale features, 79.34% accuracy for HOG features and 80.0% for Combined feature extraction.Next I applied the VGG-19 pre-trained model and got 96.74% accuracy.At last, I applied a GradCam explainable AI method to interpret the results generated from VGG19.From all these experiments, I got the best accuracy for the VGG19 pretrained model.That’s why I used Grad Cam on the VGG19 results for getting the explanation for the predictions.