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[PDF][PDF] A survey on large language models: Applications, challenges, limitations, and practical usage
Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
[PDF][PDF] Large language models: a comprehensive survey of its applications, challenges, limitations, and future prospects
Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
Natural language-assisted sign language recognition
Sign languages are visual languages which convey information by signers' handshape,
facial expression, body movement, and so forth. Due to the inherent restriction of …
facial expression, body movement, and so forth. Due to the inherent restriction of …
Masa: Motion-aware masked autoencoder with semantic alignment for sign language recognition
Sign language recognition (SLR) has long been plagued by insufficient model
representation capabilities. Although current pre-training approaches have alleviated this …
representation capabilities. Although current pre-training approaches have alleviated this …
TMS-Net: A multi-feature multi-stream multi-level information sharing network for skeleton-based sign language recognition
Abstract Sign Language Recognition (SLR) is an increasingly popular research topic due to
its extensive potential applications, such as education, healthcare, emergency response …
its extensive potential applications, such as education, healthcare, emergency response …
Prior-aware cross modality augmentation learning for continuous sign language recognition
Continuous sign language recognition (CSLR) aims to map a sign video into a sentence of
text words in the same order as the signs. Generally, word error rate (WER), ie, editing …
text words in the same order as the signs. Generally, word error rate (WER), ie, editing …
A signer-independent sign language recognition method for the single-frequency dataset
T Liu, T Tao, Y Zhao, M Li, J Zhu - Neurocomputing, 2024 - Elsevier
Currently, there are over 70 million people worldwide using more than 300 sign languages
for communication, resulting in a vast number of sign language categories. Sign language …
for communication, resulting in a vast number of sign language categories. Sign language …
Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions
D Mahmud, H Hajmohamed… - IEEE Transactions …, 2025 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITS) are crucial for the development and operation of
smart cities, addressing key challenges in efficiency, productivity, and environmental …
smart cities, addressing key challenges in efficiency, productivity, and environmental …
Sign language recognition: A comprehensive review of traditional and deep learning approaches, datasets, and challenges
T Tao, Y Zhao, T Liu, J Zhu - IEEE Access, 2024 - ieeexplore.ieee.org
The Deaf are a large social group in society. Their unique way of communicating through
sign language is often confined within their community due to limited understanding by …
sign language is often confined within their community due to limited understanding by …
StepNet: Spatial-temporal part-aware network for isolated sign language recognition
The goal of sign language recognition (SLR) is to help those who are hard of hearing or deaf
overcome the communication barrier. Most existing approaches can be typically divided into …
overcome the communication barrier. Most existing approaches can be typically divided into …