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  Published Paper Details:

  Paper Title

IMAGE SEGMENTATION USING THE R-CNN ARCHITECTURE

  Authors

  Abhinav Aggarwal,  Shikhar Yadav,  Shobhit Srivastava,  Chahat Agarwal,  Ankita Singh

  Keywords

Convolutional Neural Networks (CNNs), Convolutional Neural Networks (CNNs), Labelled Data, Binary Masks, Computer Vision.

  Abstract


In this project, with applications including scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, among many others, image segmentation is the main key topic in this project's use of computer vision and image processing. In the literature, a number of picture segmentation methods have been created. A common label is given to all the visual components or pixels that fall under the same category. In addition to the class label and object bounding box, the Mask R-CNN returns the binary object mask as well. In terms of segmenting pixels, Mask R-CNN is effective.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2305411

  Paper ID - 236686

  Page Number(s) - d165-d173

  Pubished in - Volume 11 | Issue 5 | May 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Abhinav Aggarwal,  Shikhar Yadav,  Shobhit Srivastava,  Chahat Agarwal,  Ankita Singh,   "IMAGE SEGMENTATION USING THE R-CNN ARCHITECTURE", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 5, pp.d165-d173, May 2023, Available at :http://www.ijcrt.org/papers/IJCRT2305411.pdf

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ISSN: 2320-2882
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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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