CFP last date
20 January 2025
Reseach Article

Supervised Deep Machine Learning Methods of Floral Data Image Processing

by R. Lakshmi Priya, M. Salomi, N. Manjula Devi, Manimannan G.
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

@article{ 10.5120/ijca2020920913,
author = { R. Lakshmi Priya, M. Salomi, N. Manjula Devi, Manimannan G. },
title = { Supervised Deep Machine Learning Methods of Floral Data Image Processing },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2020 },
volume = { 175 },
number = { 35 },
month = { Dec },
year = { 2020 },
issn = { 0975-8887 },
pages = { 47-52 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number35/31681-2020920913/ },
doi = { 10.5120/ijca2020920913 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:40:24.143390+05:30
%A R. Lakshmi Priya
%A M. Salomi
%A N. Manjula Devi
%A Manimannan G.
%T Supervised Deep Machine Learning Methods of Floral Data Image Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 35
%P 47-52
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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

References
  1. Krishna Kant Singh, Akansha Singh (2010) ,A Study Of Image Segmentation Algorithms For Different Types Of Images IJCSI International Journal of Computer Science.
  2. G. E. Hinton and R. R. Salakhutdinov (2206), American Association for Advancement of Science, Volume..313
  3. R. C. Gonzalez and R. E. Woods, Digital Image Processing (Tekhnosphera, Moscow, 2006) [Russian translation].
  4. P. A. Chochia (2014), “Image Segmentation Based on the Analysis of Distances in an Attribute Space,” Avtometriya 50 (6), 97–110 (2014) [Optoelekron. Instrum. Data Process. 50 (6), 613–624..
  5. I. A. Pestunov and Yu. N. Sinyavskii (2012) “Clustering Algorithms in Problems of Segmentation of Satellite Images,” Vestn. KemGU 2 (4(52)), 110–125 (2012).
  6. R. Xu and D. I. Wunsch (2005) “Survey of Clustering Algorithms,” IEEE Trans. Neural Networks 16 (3), 645–678..
  7. A. K. Jain (2010) “Data Clustering: 50 years Beyond K-Means,” Pattern Recognition. Lett. 31 (8), 651–666..
  8. P. Hope, L. Hall, and D. Goldgof (2009), “A Scalable Framework for Cluster Ensembles,” Pattern Recognition . 42 (5), 676–688..
  9. R. Kashef and M. Kamel (2011) “Cooperative Clustering,” Patt. Recogn. 43 (7), 2315–2329 (2010).
  10. J. Jia, B. Liu, and L. Jiao, “Soft Spectral Clustering Ensemble Applied to Image Segmentation,” Front. Comput. Sci. China. 5 (1), 66–78..
  11. A. Mirzaei and M. Rahmati (2010) “A Novel Hierarchical-Clustering-Combination Scheme Based on Fuzzy-Similarity Relations,” IEEE Trans. Fuzzy Syst. 18 (1), 27–39.
  12. R. A. Johnson D. W. Wichern (2009), Applied multivariate Statistical Analysis, Fifth Edition , Published by PHI Learning Private Lts. India,
  13. Everit B. S. (1993), Cluster Analysis, Third Edition, London Edward Arnold.
  14. Manimannan G, et, al. (2020), Machine Learning Method of Image Processing and Embedding of Flowers using Pattern Recognition, International Journal of Innovative and Mathematical Research, pp.12-21, India.
Index Terms

Computer Science
Information Sciences

Keywords

Image Processing Image Embedded Data Mining Hierarchical Clustering Cosine Distance and Image Visualization.