# Live American Sign Language Letter Classification with Convolutional Neural Networks

arXiv: https://arxiv.org/abs/2305.17192 · HTML: https://mlsanity.com/paper/2305.17192/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 7 references that are in the map.
- First posted on arXiv 26 May 2023.

## Builds on (most cited first, 2 of 2)

- [A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasets](https://mlsanity.com/paper/2204.03328/) (2022)
- [Using Deep Convolutional Networks for Gesture Recognition in American Sign Language](https://mlsanity.com/paper/1710.06836/) (2017)

## Abstract (arXiv)

This project is centered around building a neural network that is able to recognize ASL letters in images, particularly within the scope of a live video feed. Initial testing results came up short of expectations when both the convolutional network and VGG16 transfer learning approaches failed to generalize in settings of different backgrounds. The use of a pre-trained hand joint detection model was then adopted with the produced joint locations being fed into a fully-connected neural network. The results of this approach exceeded those of prior methods and generalized well to a live video feed application.