Supervised by Dr. Sara Baber Sial and Co-Supervised by Dr. Osman Hasan, Dr. Neelma Naz has successfully defended her PhD thesis in Human-Centric AI, titled: “Novel Scalable Skeleton-Based Dynamic Sign Language Recognition by Learning Attention-Enhanced Efficient Spatio-Temporal Features” Her research tackles the complexities of Sign Language Recognition (SLR) with a groundbreaking framework that integrates a Graph Convolutional Network (GCN) with bottleneck layer structures and residual connections.
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