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Dae-ha Yoo

dblp:331/1733 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · none

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

Computer networks · 1 · 1 first-author · 1 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.

Computer networks
1 paper
Wireless sensing and localization · 100%

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

TopicWeightPapersLastEvidence papers
Wireless sensing and localization › indoor localization
image-based localization
0.612022
A vision-based indoor positioning systems utilizing computer aided design drawing · MobiCom 2022
Wireless sensing and localization
indoor localization
0.612022
A vision-based indoor positioning systems utilizing computer aided design drawing · MobiCom 2022

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

computer vision · 0.6CAD drawing matching · 0.6
YearPublicationVenuePosition
2022 A vision-based indoor positioning systems utilizing computer aided design drawing
abstract
In recent years, with the increase in users' demand for location services, the research of Indoor Positioning Systems (IPS) has attracted much attention. Many researchers proposed schemes to estimate the user's location based on the Received Signal Strength Indicator (RSSI) values of wireless technologies. However, the RSSI value is affected by signal interference seriously. This causes the accuracy of the positioning to be greatly reduced. To solve this problem, we use Computer Vision (CV) to replace traditional solutions in this paper. CV is known for its high performance and low complexity. The proposed scheme is capable of inferring the current location of users in the possible candidates from the interior structural features of buildings captured by cameras and Computer-Aided Design (CAD) drawing.
Dae-ha Yoo, Gaoyang Shan, Byeong-Hee Roh
MobiCom1