Results 191 to 200 of about 20,260 (228)

SLRNet: A Real-Time LSTM-Based Sign Language Recognition System

arXiv.org
Sign Language Recognition (SLR) plays a crucial role in bridging the communication gap between the hearing-impaired community and society. This paper introduces SLRNet, a real-time webcam-based ASL recognition system using MediaPipe Holistic and Long ...
Sharvari Kamble
semanticscholar   +1 more source

Cross-Modal Adaptive Prototype Learning for Continuous Sign Language Recognition

IEEE transactions on circuits and systems for video technology (Print)
Continuous sign language recognition technology enables effective communication for hearing-impaired individuals by recognizing and interpreting sign language.
Dong Wei, Xuhua Yang, Yiyang Weng, Xuanyu Lin, Hong-Xiang Hu, Sheng Liu   +5 more
semanticscholar   +1 more source

C²SLR: Consistency-enhanced Continuous Sign Language Recognition

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
Ronglai Zuo, Brian Mak
openaire   +1 more source

Isharah: A Large-Scale Multi-Scene Dataset for Continuous Sign Language Recognition

arXiv.org
Current benchmarks for sign language recognition (SLR) focus mainly on isolated SLR, while there are limited datasets for continuous SLR (CSLR), which recognizes sequences of signs in a video.
Sarah N. Alyami, Hamzah Luqman, Sadam Al-Azani, Maad Alowaifeer, Y. Alharbi, Yaser Alonaizan   +5 more
semanticscholar   +1 more source

Breaking the Barriers: Video Vision Transformers for Word-Level Sign Language Recognition

arXiv.org
Sign language is a fundamental means of communication for the deaf and hard-of-hearing (DHH) community, enabling nuanced expression through gestures, facial expressions, and body movements. Despite its critical role in facilitating interaction within the
Alexander Brettmann, Jakob Grävinghoff, Marlene Rüschoff, Marie Westhues   +3 more
semanticscholar   +1 more source

BdSLW401: Transformer-Based Word-Level Bangla Sign Language Recognition Using Relative Quantization Encoding (RQE)

arXiv.org
Sign language recognition (SLR) for low-resource languages like Bangla suffers from signer variability, viewpoint variations, and limited annotated datasets.
Husne Ara Rubaiyeat, Njayou Youssouf, Md. Kamrul Hasan, Hasan Mahmud   +3 more
semanticscholar   +1 more source

MSE-GCN: A Multiscale Spatiotemporal Feature Aggregation Enhanced Efficient Graph Convolutional Network for Dynamic Sign Language Recognition

IEEE Transactions on Emerging Topics in Computational Intelligence
Graph convolution networks have emerged as an active area of research for skeleton-based sign language recognition (SLR). One essential problem in this approach is to efficiently extract the most discriminative features capable of modeling short-range ...
Neelma Naz, Hasan Sajid, Sara Ali, Osman Hasan, Muhammad Khurram Ehsan   +4 more
semanticscholar   +1 more source

GSR-Fusion: A Deep Multimodal Fusion Architecture for Robust Sign Language Recognition Using RGB, Skeleton, and Graph-Based Modalities

IEEE Access
Sign Language Recognition (SLR) plays a critical role in bridging communication gaps between the deaf and hearing communities. This research introduces GSR-Fusion, a deep multimodal fusion architecture that combines RGB-based, skeleton-based, and graph ...
Wuttichai Vijitkunsawat, Teeradaj Racharak   +1 more
semanticscholar   +1 more source

Sign Language Recognition—Dataset Cleaning for Robust Word Classification in a Landmark-Based Approach

IEEE Access
Communication barriers between hard-of-hearing and hearing individuals can be mitigated through advancements in sign language recognition (SLR) systems.
P. Antonowicz, David Kasperek, Michał Podpora   +2 more
semanticscholar   +1 more source

A Closer Look at Skeleton-Based Continuous Sign Language Recognition

2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Skeleton-based Sign Language Recognition (SLR) has emerged as a promising alternative to video-based approaches, offering robustness to visual noise, enhanced privacy, and reduced computational overhead, making it suitable for real-world deployment ...
Yuecong Min, Yifan Yang, Peiqi Jiao, Zixi Nan, Xilin Chen   +4 more
semanticscholar   +1 more source