Veuillez utiliser cette adresse pour citer ce document : https://hdl.handle.net/20.500.12394/16441
Titre: Data Glove-Based Sign Language Translation with Convolutional Neural Networks
Auteur(s): Castillo Cervera, Marco Antonio
Lopez Meza, Diego Aldair
Huamanchahua Canchanya, Deyby Maycol
metadata.dc.contributor.advisor: Huaytalla Pariona, Jaime Antonio
Mots-clés: Reconocimiento de lenguaje de señas (SLR)
Guante de datos
Editeur: Universidad Continental
Date de publication: 2024
metadata.dc.date.available: 5-fév-2025
Référence bibliographique: Castillo, M., Lopez, D. y Huamanchahua , D. (2024). Data Glove-Based Sign Language Translation with Convolutional Neural Networks. Tesis para optar el título profesional de Ingeniero Mecatrónico, Escuela Académico Profesional de Ingeniería Mecatrónica, Universidad Continental, Huancayo, Perú.
metadata.dc.identifier.doi: https://doi.org/10.1109/CMAEE58250.2022.00020
Résumé: This research was carried out because of the communication barriers that currently exist between hearing impaired and hearing people. These barriers hinder their integration into society and affect their interpersonal relationships. The objective of the study was to propose the development of a stationary assistive robot capable of displaying sign language interpretation through the combination of data gloves and the D- CNN and LSTM algorithm to facilitate the communication of hearing-impaired children in Huancayo. The triple diamond research design was used, where the mind map and the lotus diagram were used for the delimitation and definition of the problem. In addition, the IDEF0 technique was used to obtain a structured design of the project system. A morphological matrix was also used to choose the best solution for the problem. The chosen design contemplates the use of an Arduino UNO, flex sensors, accelerometers and gyroscopes for sign detection. The main algorithm consists of the union of a deep convolutional neural network and a LSTM for a correct sign classification module. The proposed design proposes to visualize the conceptual development of the project mentioned above.
metadata.dc.relation: https://ieeexplore.ieee.org/document/10066103
Extension: p. 67-74
metadata.dc.rights.accessRights: Acceso abierto
metadata.dc.source: Universidad Continental
Repositorio Institucional - Continental
Collection(s) :Tesis

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