AI Based Crop Identification Application

Abstract

Plants are the most important and primary food resource of many living things like humans, birds, animals, insects, etc. Owing to the increasing world population and decreasing food resources, nature forces us to improve the efficiency in the agricultural fields. Many Modern Computing Technologies are emerged and are get implemented in various domains of agriculture. We know that there are numerous types of plant species available on the earth. Identifying the name of those plants manually is time-consuming. Automating this using a Classification algorithm will help Biologists, Students, environmentalists, etc. in various ways. This system i.e. AI-Based Crop Identification is developed to identify the name of Field Crop Images. Convolutional Neural Network is an Artificial Intelligence algorithm based on multi-layer neural networks that learn relevant features from images, being capable of performing several tasks like image classification, object detection, and segmentation. CNN or ConvNet is implemented in this system to learn the features in the input images by sequentially entering several layers like Convolution, Activation function (RELU), Pooling, and Flattening. Finally, this system classifies new images precisely with just a few examples in the training set. Agriculture crop images from the Kaggle dataset are used to train this algorithm.