Flower Image Classification: A Review

Sakshi Dixit , Arun Jhapate , Dr. Ritu Shrivastava

Image classification, Deep learning, Flower classification, Transfer learning, Neural network.

The categorization of flower images is a difficult subject in computer vision since there are so many different types of flowers and the visual qualities of flowers are so much more complicated than other things. Convolutional neural networks (CNNs), in particular, have developed as effective tools for handling this job in recent years. Deep learning methods have also emerged as useful tools. The purpose of this paper is to offer an overview of several strategies and methodologies that are currently being used in floral picture categorization via the use of deep learning.

Published Paper   E-Certificate

"Flower Image Classification: A Review", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.9, Issue 5, page no.94 - 97, May-2024, Available :https://ijsdr.org/papers/IJSDR2405012.pdf

Volume 9 Issue 5, May-2024

Pages : 94 - 97

Paper Reg. ID: IJSDR_211072

Published Paper Id: IJSDR2405012

Downloads: 000347377

Research Area: Engineering

Country: Bhopal, Madhya Pradesh, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2405012

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2405012

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition