Deep learning in vision-based static hand gesture recognition

By Oyebade Kayode Oyedotun, Adnan Khashman. Neural computing & applications (Print), 2017

329 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Developmental and Educational Psychology, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/c5abf9479dc2bf9dddba876980745c4eee8d338b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. L. Dang
2. Kyungbok Min
3. Hanxiang Wang
4. Md. Jalil Piran
5. Cheol Hee Lee
6. Hyeonjoon Moon
7. Sakorn Mekruksavanich

Citations in the corpus

• Sensor-based and vision-based human activity recognition: A comprehensive survey (2020, methodology): “For example, Oyedotun et al. trained a stacked autoencoder-based convolutional neural network (CNN) on a public ASL static hand gesture dataset containing 24 hand gestures [12] .”