AI4Space21
* *AI for Space
* AI for dating stars: a benchmarking study for gyrochronology
* AI4MARS: A Dataset for Terrain-Aware Autonomous Driving on Mars
* Autonomous Planetary Landing via Deep Reinforcement Learning and Transfer Learning
* Event-based spacecraft landing using time-to-contact
* From Rocks to Walls: a Model-free Reinforcement Learning Approach to Dry Stacking with Irregular Rocks
* Improving Astronomy Image Quality Through Real-time Wavefront Estimation
* Investigating Spiking Neural Networks for Energy-Efficient On-Board AI Applications. A Case Study in Land Cover and Land Use Classification
* LSPnet: A 2D Localization-oriented Spacecraft Pose Estimation Neural Network
* Monocular Pose Estimation Case Study: The Hayabusa2 Minerva-II2 Deployment, A
* MRSCAtt: A Spatio-Channel Attention-Guided Network for Mars Rover Image Classification
* On-Orbit Inspection of an Unknown, Tumbling Target using NASA's Astrobee Robotic Free-Flyers
* Spacecraft Dataset for Detection, Segmentation and Parts Recognition, A
* Spacecraft Time-Series Anomaly Detection Using Transfer Learning
* SPACESeg: Automated Detection of Bed Junction Morphologies Indicating Signs of Life in Ediacaran Period
* Spot the GEO Satellites: From Dataset to Kelvins SpotGEO Challenge
* Vision-based Neural Scene Representations for Spacecraft
* Visual SLAM for Asteroid Relative Navigation
18 for AI4Space21
AI4Space22
* *AI for Space
* Asynchronous Kalman Filter for Event-Based Star Tracking
* CubeSat-CDT: A Cross-Domain Dataset for 6-DoF Trajectory Estimation of a Symmetric Spacecraft
* Data Lifecycle Management in Evolving Input Distributions for Learning-based Aerospace Applications
* End-to-end Neural Estimation of Spacecraft Pose with Intermediate Detection of Keypoints
* Globally Optimal Event-Based Divergence Estimation for Ventral Landing
* Improving Contrastive Learning on Visually Homogeneous Mars Rover Images
* MaRF: Representing Mars as Neural Radiance Fields
* Mixed-Domain Training Improves Multi-Mission Terrain Segmentation
* Monocular 6-DoF Pose Estimation for Non-cooperative Spacecrafts Using Riemannian Regression Network
* Spacecraft Pose Estimation Based on Unsupervised Domain Adaptation and on a 3D-Guided Loss Combination
* Strong Gravitational Lensing Parameter Estimation with Vision Transformer
* Transfer Learning for On-Orbit Ship Segmentation
* Using Moffat Profiles to Register Astronomical Images
14 for AI4Space22
AI4Space24
* *AI for Space
* CroSpace6D: Leveraging Geometric and Motion Cues for High-Precision Cross-Domain 6DoF Pose Estimation for Non-Cooperative Spacecrafts
* Cross-Temporal Spectrogram Autoencoder (CTSAE): Unsupervised Dimensionality Reduction for Clustering Gravitational Wave Glitches
* Deploying Machine Learning Anomaly Detection Models to Flight Ready AI Boards
* Dual-Mode Approach for Vision-Based Navigation in a Lunar Landing Scenario, A
* Exploring AI-Based Satellite Pose Estimation: from Novel Synthetic Dataset to In-Depth Performance Evaluation
* Mitigating Challenges of the Space Environment for Onboard Artificial Intelligence: Design Overview of the Imaging Payload on SpIRIT
* Monocular 6-DoF Pose Estimation of Spacecrafts Utilizing Self-iterative Optimization and Motion Consistency
* Optimized Martian Dust Displacement Detection Using Explainable Machine Learning
* Revisiting the Domain Gap Issue in Non-cooperative Spacecraft Pose Tracking
* Robust Perspective-n-Crater for Crater-based Camera Pose Estimation
* Tackling the Satellite Downlink Bottleneck with Federated Onboard Learning of Image Compression
* Transformers for Orbit Determination Anomaly Detection and Classification
13 for AI4Space24