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Joseph Telaak

dblp:377/0667 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0004-1152-8860ORCID · reported

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

Computer networks · 1 · 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.

Artificial intelligence
1 paper
3D vision · 77% Autonomous driving · 12% Robot navigation and mapping · 12%
Computer networks
1 paper
Wireless sensing and localization · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › 3d object detection › 3d object localization
3d bounding box estimation
0.812024
Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024
Computer vision › 3D vision
3d object detection
0.812024
Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024
Wireless sensing and localization
mmwave sensing
0.812024
Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024
Wireless sensing and localization › target sensing
vehicle detection
0.812024
Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024
Robotics › Autonomous driving
perception
0.212024
Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024
Robotics › Robot navigation and mapping
sensor fusion
0.212024
Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024

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

mmwave radar signal processing · 1.5
YearPublicationVenuePosition
2024 Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles
abstract
We propose AutoSense, a millimeter-wave (mmWave) wireless signal-based system for predicting 3D bounding boxes of vehicles. While cameras and LiDAR can be adversely affected by challenging weather conditions such as heavy rain, fog, or snow, mmWave signals are less susceptible to these environmental factors, making them more resilient. As a result, AutoSense can complement other sensors for accurate 3D bounding box predictions in all weather conditions.
Hem Regmi, Reza Tavasoli, Joseph Telaak, Sanjib Sur 0001, Srihari Nelakuditi
MobiSys3