Results 21 to 30 of about 1,066,523 (299)
Sign Language Recognition: High Performance Deep Learning Approach Applyied To Multiple Sign Languages [PDF]
E3S Web of Conferences, 2022 In this paper we present a high performance Deep Learning architecture based on Convolutional Neural Network (CNN). The proposed architecture is effective as it is capable of recognizing and analyzing with high accuracy different Sign language datasets ...
El Zaar Abdellah +2 more
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Computer Methods and Programs in Biomedicine Update, 2022 Background: Sign language is an essential means of communication for hearing-impaired individuals. Objective: We aimed to develop an American sign language recognition dataset and use it in the deep learning model which depends on neural networks to ...
Ahmed KASAPBAŞI +3 more
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Vision-Based American Sign Language Classification Approach via Deep Learning
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Hearing-impaired is the disability of partial or total hearing loss that causes a significant problem for communication with other people in society.
Nelly Elsayed
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Timelines and Temporal Pointing in Chinese Sign Language
Glossa, 2021 We argue that Chinese Sign Language (CSL) provides new insights into temporal anaphora, as well as new puzzles. Partee (1973) showed that temporal talk in English involves abstract anaphoric mechanisms akin to pronouns, although with a very different ...
Hao Lin +3 more
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Revisiting gradability in American Sign Language (ASL)
Glossa, 2023 This paper addresses gradability in American Sign Language (ASL). The literature has argued that languages may or may not introduce degree variables, i.e., there is cross-linguistic variation as to whether languages should be analyzed as degree- or ...
Christopher Kurz +3 more
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American Sign Language Recognition Combining with Bi-2DPCA and CNN [PDF]
Jisuanji gongcheng, 2021 The existing algorithms for American Sign Language(ASL) recognition are limited in the recognition accuracy, and require much time for model training.To address the problem, a Bayesian Optimization(BO)-based algorithm that combines Bidirectional Two ...
YANG Mingyu, YE Chunming
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Frontiers in Psychology, 2018 Considerable evidence now shows that all languages, signed and spoken, exhibit a significant amount of iconicity. We examined how the visual-gestural modality of signed languages facilitates iconicity for different kinds of lexical meanings compared to ...
Marcus Perlman +3 more
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RMUTL Engineering Journal, 2020 Most image classification is based on applying decision-making algorithms, in conjunction with image preprocessing, in order to extract distinctive features from the images and compute the most appropriate weights used in the decision making.
Chokemongkol Nadee, Krisda Yingkayun
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The ASL-CDI 2.0: an updated, normed adaptation of the MacArthur Bates Communicative Development Inventory for American Sign Language [PDF]
, 2020 Vocabulary is a critical early marker of language development. The MacArthur Bates Communicative Development Inventory has been adapted to dozens of languages, and provides a bird’s-eye view of children’s early vocabularies which can be informative for ...
Caselli, Naomi K. +2 more
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Time Is Ripe to Make Interactional Moves: Bringing Evidence From Four Languages Across Modalities
Frontiers in Communication, 2022 Sign language linguistics has largely focused on lexical, phonological, and morpho-syntactic structures of sign languages, leaving the facets of interaction overlooked. One reason underlying the study of smaller units in the initial stages of development
Alysson Lepeut, Emily Shaw
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