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Johan Wahlström

14 papers hereh-index 171.3k citations49 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author7
  • middle author2
  • last author5

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • eess.SP5
  • cs.CV2
  • cs.LG2
  • cs.AI1
  • cs.CR1
  • cs.CY1
same name
  • Johan Wahlström — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162026
most citedAdversarial Driving: Attacking End-to-End Autonomous Driving

38 citations · 65 across the 11 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

eess.SP2019★ 4 cited

FootSLAM meets Adaptive Thresholding

Johan Wahlstrom, Andrew Markham, Niki Trigoni

Calibration of the zero-velocity detection threshold is an essential prerequisite for zero-velocity-aided inertial navigation. However, the literature is lacking a self-contained c…

eess.SP2019

Sensor Fusion for Magneto-Inductive Navigation

Johan Wahlström, Manon Kok, Pedro Porto Buarque de Gusmao +3

Magneto-inductive navigation is an inexpensive and easily deployable solution to many of today's navigation problems. By utilizing very low frequency magnetic fields, magneto-induc…

cs.CV2019★ 2 cited

DeepTIO: A Deep Thermal-Inertial Odometry with Visual Hallucination

Muhamad Risqi U. Saputra, Pedro P. B. de Gusmao, Chris Xiaoxuan Lu +7

Visual odometry shows excellent performance in a wide range of environments. However, in visually-denied scenarios (e.g. heavy smoke or darkness), pose estimates degrade or even fa…

eess.SP2019

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…

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