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Found 8 papers, 4 papers with code
Federated Learning for Traffic Flow Prediction with Synthetic Data Augmentation
Deep-learning based traffic prediction models require vast amounts of data to learn embedded spatial and temporal dependencies.
Improved User Identification through Calibrated Monte-Carlo Dropout
Our thorough evaluation and comparison of different calibration methods have shown improved accuracy in user identification across multiple datasets.
Superior Scoring Rules for Probabilistic Evaluation of Single-Label Multi-Class Classification Tasks
Traditional scoring rules like Brier Score and Logarithmic Loss sometimes assign better scores to misclassifications in comparison with correct classifications.
Uncertainty Quantification to Enhance Probabilistic Fusion Based User Identification Using Smartphones
User identification through smartphones and wearable sensors holds promise but faces challenges from variability in user activities and sampling windows.
Driver Identification by an Ensemble of CNNs Obtained from Majority-Voting Model Selection
Driver identification refers to the task of identifying the driver behind the wheel among a set of drivers.
Discrete Wavelet Transform for Generative Adversarial Network to Identify Drivers Using Gyroscope and Accelerometer Sensors
After extracting features from smartphone-embedded sensors, various machine learning methods can be used to identify the driver.
Fifteen Years of Progress at Zero Velocity: A Review
Fifteen years have passed since the publication of Foxlin's seminal paper "Pedestrian tracking with shoe-mounted inertial sensors".
DeepTIO: A Deep Thermal-Inertial Odometry with Visual Hallucination
The hallucination network is taught to predict fake visual features from thermal images by using Huber loss.
