Leaf Diseases Detection using Android Kotlin App with Deep Learning Algorithm

An Android app is being created using Kotlin to support the agricultural industry. Leaf issues might be brought on by a shortage of nutrients, fungi, diseases, or insects. The most typical bacterial, fungal, and viral diseases. To ddetermine the characteristics of the disease spot quantitatively in accordance with its colour, texture, shape, and other elements. We will find and recognize leaf disease using Deep Learning (DL) approaches. One of the techniques employed in this study to detect leaf disease is deep convolutional neural networks (Deep-CNN) with a pre-trained DL model called ResNet-50. Images are categorized using the TensorFlow image classification model. All of these parameters have been taken into consideration when developing a deep-CNN-based disease detection model for leaves using Keras. The ResNet-50 model then processes the testing data set using the validation parameters it has learned. We may take a leaf image from the camera and choose it from the gallery to use as input for the software, which will then determine what kind of ailment the leaf has as well as whether it is healthy or not.