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Isolated Video-Based Sign Language Recognition Using a Hybrid CNN-LSTM Framework Based on Attention Mechanism
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Outgoing claims: the papers this work cites, builds on, or argues with.
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inferred← citeshttps://doi.org/10.2139/ssrn.6218106openalex-snapshot
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inferred← citeshttps://doi.org/10.2139/ssrn.6864645openalex-snapshot
CAGTN: A Lightweight Confidence-Aware Graph-Temporal Network for Sign Language Recognition in Resource-Constrained Settings
inferred← citeshttps://doi.org/10.26634/jse.19.2.21389openalex-snapshot
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inferred← citeshttps://doi.org/10.32628/cseit261219openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/frai.2025.1630743openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/app152312622openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/jimaging12080357openalex-snapshot
A Comprehensive Review of SLR Systems: Challenges, Datasets, and Unresolved Gaps
inferred← citeshttps://doi.org/10.3390/mti10060058openalex-snapshot
A Comprehensive Review of Deep Learning Approaches for Video-Based Sign Language Recognition: Datasets, Challenges and Insights
inferred← citeshttps://doi.org/10.3390/s26010027openalex-snapshot
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inferred← citeshttps://doi.org/10.35940/ijese.l2628.14011225openalex-snapshot
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inferred← citeshttps://doi.org/10.53759/7669/jmc202505185openalex-snapshot
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inferred← citeshttps://doi.org/10.54381/icp.2025.1.08openalex-snapshot
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inferred← citeshttps://doi.org/10.5565/rev/elcvia.2317openalex-snapshot
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inferred← citeshttps://doi.org/10.57197/jdr-2024-0051openalex-snapshot
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inferred← citeshttps://doi.org/10.66261/56qhw573openalex-snapshot
A Comprehensive Review of Machine Learning and Deep Learning Techniques for Sign Language Recognition.
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