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Luis Sobral

dblp:126/4693 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1996
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

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
Image recognition and object detection · 50% Robot navigation and mapping · 50%
Computer graphics and multimedia
1 paper
Audio and music processing · 100%

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

TopicWeightPapersLastEvidence papers
Computer vision › Image recognition and object detection
object recognition
0.011996
Ultrasonic detection in robotic environments · ICRA 1996
Robotics › Robot navigation and mapping › acoustic sensing
ultrasonic sensing
0.011996
Ultrasonic detection in robotic environments · ICRA 1996
Audio and music processing
acoustic signal processing
0.011996
Ultrasonic detection in robotic environments · ICRA 1996

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

state-space realization · 0.0least squares · 0.0impulse response analysis · 0.0clustering · 0.0
YearPublicationVenuePosition
1996 Ultrasonic detection in robotic environments
abstract
Based on information produced by a 200 kHz ultrasonic echo device developed for robotics and other industrial purposes, a method for object identification was developed and is presented in this paper. Interpretation of the echos from the reflecting objects, complexity analysis and information extraction were made by system identification methods such as impulse response analysis and state-space realization. A clustering-type discrimination of different objects based on the echo identification result was made in a subsequent step using the least-squares method. Experimental evaluation showed that the method is effective for object recognition.
Luis Sobral, Rolf Johansson 0001, Gunnar Lindstedt, Gustaf Olsson
ICRA1