# Entrenamiento de una red neuronal para el reconocimiento de imagenes de lengua de senas capturadas con sensores de profundidad

Source: [Entrenamiento de una red neuronal para el reconocimiento de imagenes de lengua de senas capturadas con sensores de profundidad](<https://www.sota2.com/research/paper/68fa64311e209131cea035fd>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T20:59:11.405Z

Authors: Rivas P. Pedro E., Velarde-Anaya Omar, Gonzalez-Lopez Samuel, Rivas P. Pablo, Alvarez-Torres Norma Angelica

Published: 2018-03-22T05:40:28.000Z

## Abstract

Due to the growth of the population with hearing problems, devices have been developed that facilitate the inclusion of deaf people in society, using technology as a communication tool, such as vision systems. Then, a solution to this problem is presented using neural networks and autoencoders for the classification of American Sign Language images. As a result, 99.5% accuracy and an error of 0.01684 were obtained for image classification

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1804.00508>)

[PDF](<https://arxiv.org/pdf/1804.00508.pdf>)