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Found 4 papers, 0 papers with code
Robust Monocular Localization of Drones by Adapting Domain Maps to Depth Prediction Inaccuracies
We present a novel monocular localization framework by jointly training deep learning-based depth prediction and Bayesian filtering-based pose reasoning.
MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence
Using Bayesian inference, not only the prediction itself, but the prediction confidence can also be extracted for planning risk-aware actions.
Probabilistic Localization of Insect-Scale Drones on Floating-Gate Inverter Arrays
Addressing the computational challenges of localization in an insect-scale drone using a CIM approach, we propose a novel framework of 3D map representation using a harmonic mean of "Gaussian-like" mixture (HMGM) model.
Indoor Localization
Robotics
Hardware Architecture
Image and Video Processing
B.7; I.2.9
$MC^2RAM$: Markov Chain Monte Carlo Sampling in SRAM for Fast Bayesian Inference
This work discusses the implementation of Markov Chain Monte Carlo (MCMC) sampling from an arbitrary Gaussian mixture model (GMM) within SRAM.
