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Machine Learning Model for Text-Based Image Analyzing Using Neural Network Training in Natural Scenes

EasyChair Preprint no. 9931

14 pagesDate: April 6, 2023

Abstract

This Research work proposes a progressed cyber-bodily systems (CPS) structure

for a clever robot manufacturing unit primarily based totally on a business cloud platform pushed

via way of means of massive information primarily based totally on the conventional CPS structure.

To complete the conceptual design, this research work uses the structure evaluation and layout

language to model and lay out a total of three scales for the underlying cell-degree robotic, the

machine-degree robotic shop, and the general robot smart manufacturing unit CPS, respectively.

For Creating a robot intelligent manufacturing facility that connects a neighborhood to a standard

CPS machine. An architecture for a business control machine for CPS cloud computing is suggested

using the advantages of cloud computing and combining robot CPS with cloud computing. Base-

based allotted garage structure with Storm primarily based allotted real-time processing structure.

The ever-growing photo library does not support traditional photo retrieval techniques. These

downsides may be eliminated via way of means of using the contents of the photo for photo

retrieval. D-SIFT works with CBIR and is centered across visible functions like shape, color, and

texture.

Keyphrases: CBIR, detection, image processing, neural networks, photo retrieval, proposed methodology, restoration frameworks

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:9931,
  author = {M Dinesh Kumar and K Manoj and P Meiyarasan and N S Nithya},
  title = {Machine Learning Model for Text-Based Image Analyzing Using Neural Network Training in Natural Scenes},
  howpublished = {EasyChair Preprint no. 9931},

  year = {EasyChair, 2023}}
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