mlsanityData to 7 Oct 2026

Deep Learning based Systems for Crater Detection: A Review

arXiv 2310.07727 ↗First posted 28 Sep 2023cs.CV eess.IVcited by 5

Not on the map. Why?

Abstract (arXiv)

Craters are one of the most prominent features on planetary surfaces, used in applications such as age estimation, hazard detection, and spacecraft navigation. Crater detection is a challenging problem due to various aspects, including complex crater characteristics such as varying sizes and shapes, data resolution, and planetary data types. Similar to other computer vision tasks, deep learning-based approaches have significantly impacted research on crater detection in recent years. This survey aims to assist researchers in this field by examining the development of deep learning-based crater detection algorithms (CDAs). The review includes over 140 research works covering diverse crater detection approaches, including planetary data, craters database, and evaluation metrics. To be specific, we discuss the challenges in crater detection due to the complex properties of the craters and survey the DL-based CDAs by categorizing them into three parts: (a) semantic segmentation-based, (b) object detection-based, and (c) classification-based. Additionally, we have conducted training and testing of all the semantic segmentation-based CDAs on a common dataset to evaluate the effectiveness of each architecture for crater detection and its potential applications. Finally, we have provided recommendations for potential future works.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 31 of its 140 references that are in the map. First posted on arXiv 28 Sep 2023.

Builds on

31 of 140 references.

References · 31

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19 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 2.

5 papers.

  1. 2026Vision-Language Model for Accurate Crater Detectioncited by 2
  2. 2024Evaluation of Resource-Efficient Crater Detectors on Embedded Systemscited by 0
  3. 2025Deep learning framework for crater detection and identification on the Moon and Marscited by 0
  4. 2025Adaptive Quantized Planetary Crater Detection System for Autonomous Space Explorationcited by 0
  5. 2026Adapting a Foundation Model for Lunar Surface Height Estimationcited by 0