A Systematic Analysis of Big Image Data Methodologies in Various Applications
Madhu M. Nayak1, Sumithra Devi K. A.2

1Madhu M. Nayak*, Department of Computer Science & Engineering, GSSS Institute of Engineering & Technology for Women, Mysuru, India.
2Sumithra Devi K. A., Department of ISE, Dayananda Sagar Academy of Technology & Management, Bengaluru, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 26, 2020. | Manuscript published on March 10, 2020. | PP: 483-487 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2307039520 /2020©BEIESP | DOI: 10.35940/ijitee.E2307.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Big data is large-scale data collected for knowledge discovery, it has been widely used in various applications. Big data often has image data from the various applications and requires effective technique to process data. In this paper, survey has been done in the big image data researches to analysis the effective performance of the methods. Deep learning techniques provides the effective performance compared to other methods included wavelet based methods. The deep learning techniques has the problem of requiring more computational time, and this can be overcome by lightweight methods. 
Keywords: Big Data, Deep Learning Techniques, Image Processing, Social Media and Wavelet Based Methods.
Scope of the Article: Deep Learning