139 citations · 649 across the 28 of their papers we have counts for
6 papers · 1 filter
Exploring Positive Noise in Estimation Theory
Kamiar Radnosrati, Gustaf Hendeby, Fredrik Gustafsson
Estimation of a deterministic quantity observed in non-Gaussian additive noise is explored via order statistics approach. More specifically, we study the estimation problem when me…
Energy-Based Models for Deep Probabilistic Regression
Fredrik K. Gustafsson, Martin Danelljan, Goutam Bhat +1
While deep learning-based classification is generally tackled using standardized approaches, a wide variety of techniques are employed for regression. In computer vision, one parti…
Asynchronous Averaging of Gait Cycles for Classification of Gait and Device Modes
Parinaz Kasebzadeh, Gustaf Hendeby, Fredrik Gustafsson
An approach for computing unique gait signature using measurements collected from body-worn inertial measurement units (IMUs) is proposed. The gait signature represents one full cy…
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision
Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön
While deep neural networks have become the go-to approach in computer vision, the vast majority of these models fail to properly capture the uncertainty inherent in their predictio…
Bayesian Cooperative Localization Using Received Signal Strength With Unknown Path Loss Exponent: Message Passing Approaches
Di Jin, Feng Yin, Carsten Fritsche +2
We propose a Bayesian framework for the received-signal-strength-based cooperative localization problem with unknown path loss exponent. Our purpose is to infer the marginal poster…
Zero-Velocity Detection - A Bayesian Approach to Adaptive Thresholding
Johan Wahlström, Isaac Skog, Fredrik Gustafsson +2
A Bayesian zero-velocity detector for foot-mounted inertial navigation systems is presented. The detector extends existing zero-velocity detectors based on the likelihood-ratio tes…