International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 175 - Number 35 |
Year of Publication: 2020 |
Authors: R. Lakshmi Priya, M. Salomi, N. Manjula Devi, Manimannan G. |
10.5120/ijca2020920913 |
R. Lakshmi Priya, M. Salomi, N. Manjula Devi, Manimannan G. . Supervised Deep Machine Learning Methods of Floral Data Image Processing. International Journal of Computer Applications. 175, 35 ( Dec 2020), 47-52. DOI=10.5120/ijca2020920913
This research paper attempts to identify the pattern of three types of images using deep machine learning methods for cluster analysis. These three different images were collected on different web domains with different pixels and under the floral head. The flowers have a basic RGB colour and Black and white colour with different Kilo Byte (KB) sizes. Python data-based software creates image Width, Height and Size. The machine-readable image embedding widget image generates a vector base database from