A 160-class, 144,000-image HamNoSys-grounded handshape benchmark is introduced with four baselines; leave-one-subject-out accuracy falls to about 45%.
InProceedings of the 21st International ACM SIGACCESS Con- ference on Computers and Accessibility, 16– 31 (Association for Computing Machinery, New York, NY, USA, 2019)
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A HamNoSys-Guided Dataset and Baselines for Fine-Grained Isolated Handshape Recognition in Sign Language
A 160-class, 144,000-image HamNoSys-grounded handshape benchmark is introduced with four baselines; leave-one-subject-out accuracy falls to about 45%.