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Found 3 papers, 2 papers with code
Transferability of Convolutional Neural Networks in Stationary Learning Tasks
To accomplish this we investigate the properties of CNNs for tasks where the underlying signals are stationary.
Deterministic Multi-sensor Measurement-adaptive Birth using Labeled Random Finite Sets
A truncation procedure has also been provided that leverages a stochastic Gibbs sampler to truncate the birth density for scalability.
Multi-Target Tracking with Transferable Convolutional Neural Networks
Multi-target tracking (MTT) is a classical signal processing task, where the goal is to estimate the states of an unknown number of moving targets from noisy sensor measurements.
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