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Volume 9 - No: 2

Based on Blockchain and Artificial Intelligence Technology: Building Crater Identification from Planetary Imagery

  • Zeren Wu Ph.D Candidate, Department of Sociology, Moscow University, Moscow, Russia.
    whiker@yeah.net
    0009-0006-6137-1587
  • A. Shitova Margarita Master, Department of Sociology, Moscow University, Moscow, Russia.
    margomorga@gmail.com
    0009-0000-2536-2823
DOI: 10.28978/nesciences.1567736
Keywords: Blockchain, artificial intelligence, crater detection, intelligence.

Abstract

Blockchain and Artificial Intelligence (AI) technology are a core force for industrial upgrading and change. Crater counting commenced with a manual enumeration of dozens, hundreds, or thousands of craters to ascertain the lifespan of geological units on planets within the solar system. Automatic crater identification methods have sought to expedite this procedure. Prior studies have utilized computer vision methodologies using manually designed features, including light and shadow trends, circle identification, and detection of edges. The study persists, with academics now employing approaches such as AI that allow the method to generate distinct characteristics autonomously. The burgeoning discipline of AI, characterized by a rapid increase in publications and methodologies, can enhance crater counting applications, mainly through collaborative multidisciplinary initiatives. The results show that integrating blockchain and AI technology can effectively promote the construction of crater detection from planetary imagery.

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Date

September 2024

Page Number

19-32