A Study of Convolutional Architectures for Handshape Recognition applied to Sign Language

1 code implementation • CACIC 2017 • Quiroga Facundo, Antonio Ramiro, Ronchetti Franco, LanzariniLaura Cristina, Rosete Alejandro

Using the LSA16 and RWTH-PHOENIX-Weather handshape datasets, we performed experiments with the LeNet, VGG16, ResNet-34 and All Convolutional architectures, as well as Inception with normal training and via transfer learning, and compared them to the state of the art in these datasets.

Hand Gesture Recognition Sign Language Recognition +1