COMPUTER VISION DETECTION OF SUBMERGED OBJECT THROUGH MACHINE LEARNING

Authors

  • Rupinder Kaur
  • Amita Kashyap
  • Dushyant Kumar

Keywords:

RGB (Red-Green-Blue), Fast-RCNN (Faster Region-Convolution Neural Network), Computer Vision.

Abstract

Object Recognition is a widely-held innovation that distinguishes examples inside an image. Inorder to eliminate the barriers in Computer Vision innovation because of the disintegration of the RGB (Red-GreenBlue) constituents with the increment inside and out,it has been a need that the precision and effectiveness of recognizing any item submerged is ideal.Inthisresearch,, we direct Submerged Item Recognition utilizing AI through Tensor stream and image Handling alongside Fast-RCNN (Faster Region-Convolution Neural Network) as a calculation for execution. An appropriate climate will be made so that AI calculation will be utilized to prepare
various pictures of the submerged object. Open source PC Vision has different capacities which can be utilized for the picture preparing needs when a picture is Open source PC Vision has different capacities which can be utilized for the image preparing needs when an object is acquire.

 

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Published

2023-12-19

How to Cite

Rupinder Kaur, Amita Kashyap, & Dushyant Kumar. (2023). COMPUTER VISION DETECTION OF SUBMERGED OBJECT THROUGH MACHINE LEARNING. Elementary Education Online, 20(5), 5013–5019. Retrieved from https://ilkogretim-online.org/index.php/pub/article/view/4246

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Section

Articles