63 citations · 196 across the 35 of their papers we have counts for
6 papers · 1 filter
Analysis of Explainers of Black Box Deep Neural Networks for Computer Vision: A Survey
Vanessa Buhrmester, David Münch, Michael Arens
Deep Learning is a state-of-the-art technique to make inference on extensive or complex data. As a black box model due to their multilayer nonlinear structure, Deep Neural Networks…
Modeling continuous-time stochastic processes using -Curve mixtures
Ronny Hug, Wolfgang Hübner, Michael Arens
Representations of sequential data are commonly based on the assumption that observed sequences are realizations of an unknown underlying stochastic process, where the learning pro…
Investigation on Combining 3D Convolution of Image Data and Optical Flow to Generate Temporal Action Proposals
Patrick Schlosser, David Münch, Michael Arens
In this paper, several variants of two-stream architectures for temporal action proposal generation in long, untrimmed videos are presented. Inspired by the recent advances in the…
Fusion of time of arrival and time difference of arrival for ultra-wideband indoor localization
Juri Sidorenko, Volker Schatz, Norbert Scherer-Negenborn +2
This article presents a new approach for the wireless clock synchronization of Decawave ultra-wideband transceivers based on the time difference of arrival. The presented technique…
Decawave UWB clock drift correction and powerself-calibration
Juri Sidorenkoab, Volker Schatza, Norbert Scherer-Negenborna +2
The position accuracy based on Decawave Ultra-Wideband (UWB) is affectedmainly by three factors: hardware delays, clock drift, and signal power. Thisarticle discusses the last two…
An RNN-based IMM Filter Surrogate
Stefan Becker, Ronny Hug, Wolfgang Hübner +1
The problem of varying dynamics of tracked objects, such as pedestrians, is traditionally tackled with approaches like the Interacting Multiple Model (IMM) filter using a Bayesian…