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  Published Paper Details:

  Paper Title

SMALL SCALE CRATER DETECTION USING DEEP LEARNING

  Authors

  M Ankeeta,  Dr. K. N. Pushpalatha

  Keywords

Crater, crater detection, deep learning, Faster R-CNN

  Abstract


The holes on planets are conceivable scene bets for top precision transport docking and vagabond course tasks. As required, it is fundamental to authoritatively confine the cavities. Studies alluded to generally think around colossal degree depressions, while restricted scope holes are similarly basic for arranging reason. Pit counting started with hand counting hundreds, thousands, or even incredible numerous cavities to choose the time of geological units on planetary collections of the planetary gathering. Electronic opening area estimations have tried to speed up this cycle. Past investigation has used PC vision systems with hand customized components, for instance, light and shadow plans, circle finding, or edge acknowledgment. In extraction of restricted scope depressions, three issues become central: (1) One ground cavity can be changed fundamentally in different pictures. (2) A pit could without an entirely momentous stretch be separated over a drawn-out period and, shockingly, be disappear into the surface. (3) The significance of cavities expands earnestly as the decline of opening size

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2208232

  Paper ID - 224389

  Page Number(s) - b803-b808

  Pubished in - Volume 10 | Issue 8 | August 2022

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  M Ankeeta,  Dr. K. N. Pushpalatha,   "SMALL SCALE CRATER DETECTION USING DEEP LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 8, pp.b803-b808, August 2022, Available at :http://www.ijcrt.org/papers/IJCRT2208232.pdf

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


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