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Sliding Window Neural Generated Tracking Based on Measurement Model
In the pursuit of further advancement in the field of target tracking, this paper explores the efficacy of a feedforward neural network in predicting drones tracks, aiming to eventually, compare the tracks created by the well-known Kalman filter and the ones created by our proposed neural network.
Towards Bundle Adjustment for Satellite Imaging via Quantum Machine Learning
Given is a set of images, where all images show views of the same area at different points in time and from different viewpoints.
Riemannian batch normalization for SPD neural networks
Covariance matrices have attracted attention for machine learning applications due to their capacity to capture interesting structure in the data.
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