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Jacqueline M. Schellberg

dblp:302/3571 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 2 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
3D vision · 100%
Computer networks
1 paper
Wireless sensing and localization · 100%
Human-computer interaction and pervasive computing
1 paper
Wearable and physiological sensing · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
depth and reconstruction		 0.612022
Accurate device self-tracking for robust millimeter-wave imaging on handheld smart devices · MobiSys 2022
Wireless sensing and localization › mmwave sensing
mmwave imaging		 0.612022
Accurate device self-tracking for robust millimeter-wave imaging on handheld smart devices · MobiSys 2022

Methods — techniques the papers use, named apart from their topics

synthetic aperture radar · 1.7camera-based tracking · 1.7
YearPublicationVenuePosition
2023 mmSight: Towards Robust Millimeter-Wave Imaging on Handheld Devices
Jacqueline M. Schellberg, Hem Regmi, Sanjib Sur 0001
 WoWMoM1
2022 Accurate device self-tracking for robust millimeter-wave imaging on handheld smart devices
abstract
Millimeter-wave (mmWave) imaging has been difficult to implement on handheld devices since imaging algorithms rely on millimeter-scale device self-tracking, which existing systems cannot achieve reliably. We propose CompenSAR, a handheld system which integrates a mmWave transceiver and a tracking camera, and overcomes the self-tracking limitations to enable handheld mmWave imaging.
Jacqueline M. Schellberg, Sanjib Sur 0001
 MobiSys1