A CNN and TF Techniques Development for Efficient Identification of Floral Recognition

This paper explores the intersection of natural beauty and technology, specifically focusing on the diverse array of flowers in India. Despite encountering numerous flowers, comprehensive knowledge remains elusive. The primary goal is to uncover unidentified flowers through innovative methodologies, addressing the knowledge gap with the transformative tool of Artificial Intelligence (AI). In this swiftly advancing era, AI, particularly leveraging Convolution Neural Networks (CNN), revolutionizes flower identification. CNNs, known for image classification efficacy, play a pivotal role in this exploration. The paper introduces CNNs through a TensorFlow image classifier for precise flower identification, promising groundbreaking strides, especially in medicine and cosmetics. This research pioneers CNN concepts, highlighting AI’s potential contributions to botanical knowledge. By showcasing CNNs as reliable tools for accurate flower identification, the interdisciplinary approach illuminates the inherent beauty of flowers. Beyond describing an application, the paper aspires to ongoing research for system enhancement, signifying a significant step in unraveling diverse flower mysteries and emphasizing AI’s transformative impact on botanical understanding.