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Introduction to the Virtual Collection on Machine Learning in Aerospace
The Causality for Climate Challenge
AI-based Wave Prediction in Complex Plasmas
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers
Examining optoelectronics in machine vision and applications in industry 4.0
Generalizability of Code Clone Detection on CodeBERT
A data-driven dynamics simulation framework for railway vehicles
Small-amplitude bogie hunting identification method for high-speed trains based on machine learning
Friction-adaptive stochastic nonlinear model predictive control for autonomous vehicles
Modeling of aircraft fuel consumption using machine learning algorithms
Modeling of aircraft fuel consumption using machine learning algorithms
Prediction of finger movements using ultrasound images
Research on the air brake system of heavy haul trains based on neural network
An Artificial Neural Network Approach to Predict Rotor-Airframe Acoustic Waveforms
Machine learning approaches for detection of robot errors in human brain signals
Data-driven train set crash dynamics simulation
Federated Learning for Spanish Ports as an Aid to Digitization
Data-Driven Approach Toward Airspace Design for Regional Air Mobility Operations in Korea
Prediction of Zenith tropospheric delay in GNSS observations using support vector regression
Surface EMG for Force Control of Mechanical Hands
Machine Learning Based Approach to a Crane Load Estimation
Optimization of Pin Fins Using Computational Fluid Dynamics and Machine Learning
Precision Mars Entry Navigation with Atmospheric Density Adaptation via Neural Networks
Tensor Voting : A Perceptual Organization Approach to Computer Vision and Machine Learning
Sensitivity and calibration of turbulence model in the presence of epistemic uncertainties
Sensitivity and calibration of turbulence model in the presence of epistemic uncertainties
Combining learning and structure for robotic manipulation
Optimizing inventory control through a data-driven and model-independent framework
Applicability of machine learning in uncertainty quantification of turbulence models
Applicability of machine learning in uncertainty quantification of turbulence models
Artificial Intelligence for Spectral Analysis: a Comprehensive Framework
Lateral Control Design for Autonomous Vehicles Using a Big Data-Based Approach
Monocular Relative Pose Estimation Pipeline for Uncooperative Resident Space Objects
Condition Monitoring of Rail Vehicle Suspension Elements: A Machine Learning Approach
Enabling Limited Resource-Bounded Disjunction in Scheduling
Using Deep Learning to Predict Unstable Approaches for General Aviation Aircraft
Railway Bogie Diagnostics Using Machine Learning and Bayesian Net Reasoning Approaches