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Luís Lima

dblp:371/5360 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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
Video understanding and tracking · 100%
Human-computer interaction and pervasive computing
1 paper
Learning and educational technologies · 100%

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

TopicWeightPapersLastEvidence papers
Computer vision › Video understanding and tracking › sign language recognition
fingerspelling recognition
0.812024
LERMO: A Novel Web Game for AI-Enhanced Sign Language Recognition · AAAI 2024
Computer vision › Video understanding and tracking
sign language recognition
0.812024
LERMO: A Novel Web Game for AI-Enhanced Sign Language Recognition · AAAI 2024

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

landmark detection · 1.5deep learning · 1.5
YearPublicationVenuePosition
2024 LERMO: A Novel Web Game for AI-Enhanced Sign Language Recognition
abstract
Sign language is a visual and gestural communication system used by deaf and hearing-impaired people. Despite numerous deep learning methods proposed for automatic interpretation, a gap persists in developing applications that effectively utilize these models for assisting sign language studies and inclusion. We introduce LERMO (https://lermo.app/), a web game merging machine learning and gamification to enhance sign language fingerspelling. Inspired by Wordle™, LERMO offers an interactive word-guessing game where users can play using a video camera. We create a new dataset of labeled landmark fingerspelling and design our model to ensure optimal speed and efficiency to run on a web browser. We survey approximately 40 users, which find LERMO user-friendly and innovative. From those, 95% believe LERMO could be used to enhance fingerspelling skills.
Adilson Medronha, Luís Lima, Janaína Claudio, Lucas S. Kupssinskü, Rodrigo C. Barros
AAAI2