A Comprehensive Analysis of Deep Learning Techniques for Recognition of Flower Species
R Shiva Shankar, L V Srinivas, VV Sivarama Raju, KVSS Murthy
20212021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV)17 citationsDOI
Abstract
Flower Species Recognition may be a difficult issue due to the wide selection of features, like leaves and grass. The classification is done by the traditional method through color, shape, texture, petals, sepals etc. The image analysis and classification has been sharply developed by Deep Learning methods. This research work considered a dataset which contains 4242 images with 5 classes by using Convolutional Neural Network (CNN) to recognize flower species with high accuracy by using framework. Tensor Flow and Image Data Generator is used to augment the training set and avoid Overfitting.
Topics & Concepts
OverfittingArtificial intelligenceComputer scienceConvolutional neural networkSepalDeep learningPattern recognition (psychology)PetalContextual image classificationImage (mathematics)Set (abstract data type)Artificial neural networkMachine learningBotanyBiologyProgramming languageStamenPollenSmart Agriculture and AILeaf Properties and Growth MeasurementSpectroscopy and Chemometric Analyses