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"Signs"
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Road signs
\"Describes common road signs you might see around town and tells what they mean. Includes visual literacy activity\"--Provided by publisher.
Book
Multi-Stream General and Graph-Based Deep Neural Networks for Skeleton-Based Sign Language Recognition
Sign language recognition (SLR) aims to bridge speech-impaired and general communities by recognizing signs from given videos. However, due to the complex background, light illumination, and subject structures in videos, researchers still face challenges in developing effective SLR systems. Many researchers have recently sought to develop skeleton-based sign language recognition systems to overcome the subject and background variation in hand gesture sign videos. However, skeleton-based SLR is still under exploration, mainly due to a lack of information and hand key point annotations. More recently, researchers have included body and face information along with hand gesture information for SLR; however, the obtained performance accuracy and generalizability properties remain unsatisfactory. In this paper, we propose a multi-stream graph-based deep neural network (SL-GDN) for a skeleton-based SLR system in order to overcome the above-mentioned problems. The main purpose of the proposed SL-GDN approach is to improve the generalizability and performance accuracy of the SLR system while maintaining a low computational cost based on the human body pose in the form of 2D landmark locations. We first construct a skeleton graph based on 27 whole-body key points selected among 67 key points to address the high computational cost problem. Then, we utilize the multi-stream SL-GDN to extract features from the whole-body skeleton graph considering four streams. Finally, we concatenate the four different features and apply a classification module to refine the features and recognize corresponding sign classes. Our data-driven graph construction method increases the system’s flexibility and brings high generalizability, allowing it to adapt to varied data. We use two large-scale benchmark SLR data sets to evaluate the proposed model: The Turkish Sign Language data set (AUTSL) and Chinese Sign Language (CSL). The reported performance accuracy results demonstrate the outstanding ability of the proposed model, and we believe that it will be considered a great innovation in the SLR domain.
Journal Article
Sign off
A wordless picture book that shows what the figures on road signs do when no one is around to see them.
Book
Protocolo en eventos protagonizados por personas sordas signantes: acto de presentación de los signos personales de Sus Altezas Reales Leonor y Sofía de Borbón
Este artículo recoge el histórico acto de presentación de los signos personales de Sus Altezas Reales la Princesa de Asturias Doña Leonor de Borbón Ortiz y de su hermana la Infanta Doña Sofía. El acontecimiento de otorgar un signo personal a tan insignes figuras supuso un hito en la historia de la comunidad Sorda, por cuanto se trató de un gran reconocimiento dado que se les regala una identidad, a modo de bautismo, que es única y personal. El génesis del acto en el que se presentaron los signo-nombre de Sus Altezas Reales supuso encontrarse con importantes dificultades y lagunas en cuanto a la organización y el protocolo a seguir debido a las características de este. Se trataba de un evento cuyos anfitriones y gran parte de los asistentes eran personas Sordas usuarias de la Lengua de Signos Española. Esta singularidad obligaba a reconsiderar, diseñar y prever circunstancias que son poco habituales en ceremonias y actos públicos a los que asisten autoridades y representantes sujetos a precedencias. La ausencia de literatura científica supuso aportar una serie de soluciones que se dieron en cuanto a la producción del evento, la puesta en escena del protocolo y las particularidades de este. Este trabajo pretende servir de guía y orientación para que otros investigadores y/o profesionales del protocolo que se encuentren en situaciones semejantes descubran nuestra experiencia, las dificultades encontradas, las soluciones que se aportaron dieron y pueda conocer a la comunidad Sorda.
Journal Article
Kanban : traditional shop signs of Japan
\"Kanban, a fusion of art and commerce, refers to the traditional signs Japanese merchants displayed on the streets to advertise their presence, denote the products and services to be found inside, as well as to give individual identity and expression to the shop itself. This book will trace the history of the shop sign in Japan, explore some of the businesses and trades represented, and help the reader travel back to the world of traditional Japan, made emblematic in the fascinating world of kanban\"-- Provided by publisher.
Book
Deepsign: Sign Language Detection and Recognition Using Deep Learning
The predominant means of communication is speech; however, there are persons whose speaking or hearing abilities are impaired. Communication presents a significant barrier for persons with such disabilities. The use of deep learning methods can help to reduce communication barriers. This paper proposes a deep learning-based model that detects and recognizes the words from a person’s gestures. Deep learning models, namely, LSTM and GRU (feedback-based learning models), are used to recognize signs from isolated Indian Sign Language (ISL) video frames. The four different sequential combinations of LSTM and GRU (as there are two layers of LSTM and two layers of GRU) were used with our own dataset, IISL2020. The proposed model, consisting of a single layer of LSTM followed by GRU, achieves around 97% accuracy over 11 different signs. This method may help persons who are unaware of sign language to communicate with persons whose speech or hearing is impaired.
Journal Article
The Hutchinson dictionary of symbols in art
Practical key to the understanding and appreciation of Western painting and sculpture.
Book
