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Edge-Optimized YOLOv11n Architecture for Offline Recognition of Nigerian Sign Language Alphanumeric Gestures
Deaf inclusion across sub-Saharan society faces regional hurdles, with Nigeria as the core empirical focus. Existing recognition models demand heavy computational infrastructure. However, standard mobile phones used locally rarely exceed 1 GB to 4 GB of RAM. This study addresses constraints through
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