crater-detection

Autonomous Lunar Orbit Navigation Using Ellipse R-CNN and Crater Pattern Matching

PyCDA: Simple Crater Detection

Implementing YOLO to detect craters on Mars

Official PyTorch implementation for IGARSS 2024 paper: "Evaluation of Resource-Efficient Crater Detectors on Embedded Systems"

Lunar Navigation is a critical component for the success of lunar missions, a multifaceted system aims to ensure safe lunar navigation through the generation of high-resolution hazard maps, employing super-resolution methods, crater detection, crater pattern matching, and visual terrain relative navigation.

Automatic crater detection on grayscale lunar PNG images using OpenCV, morphological operations, and ellipse fitting.

Lunar and Martian Crater Detection and Surface Dating Application

Convolutional Neural Network Machine Learning model in Space Exploration (Image Classification)

Highlight shadow algorithm used to generate all possible subsamples from the high quality imagery, which are to be verified using supervised algorithm such as CNN.

A deep learning–based system for Terrain Relative Navigation (TRN) that detects lunar craters using a YOLOv8 neural network and estimates crater depth and inter-crater distances for spacecraft localization.

Python pipeline for lunar crater rim detection from DEMs using D8 flow routing, sink filling, morphology filters, and profile-based rim refinement (Liu et al. 2017).

Command-line tool for multiscale crater detection using a custom-trained YOLOv8 model.

Astronomical objects craters detection by deep learning

Lunar Crater Detection using DEtection TRansformer (DETR)

Training and Learning

Automatic detection of craters on the lunar surface