A compact transformer using Mediapipe skeletal landmarks reports 90.67% accuracy on the 226-word AUTSL Turkish Sign Language recognition benchmark.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
TSLFormer: A Lightweight Transformer Model for Turkish Sign Language Recognition Using Skeletal Landmarks
A compact transformer using Mediapipe skeletal landmarks reports 90.67% accuracy on the 226-word AUTSL Turkish Sign Language recognition benchmark.