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Introduction to the Virtual Collection on Machine Learning in Aerospace
Data-Driven Approach Toward Airspace Design for Regional Air Mobility Operations in Korea
Precision Mars Entry Navigation with Atmospheric Density Adaptation via Neural Networks
Optimization of Pin Fins Using Computational Fluid Dynamics and Machine Learning
Verification of Image-Based Neural Network Controllers Using Generative Models
Monocular Relative Pose Estimation Pipeline for Uncooperative Resident Space Objects
Enabling Limited Resource-Bounded Disjunction in Scheduling
Using Deep Learning to Predict Unstable Approaches for General Aviation Aircraft
Development of a Language Model for Named-Entity-Recognition in Aerospace Requirements
Natural-Language-Processing-Enabled Quantitative Risk Analysis of Aerial Wildfire Operations