Abstract: In the context of increasing digital accessibility and the need for inclusive communication technologies, the demand for automated sign language recognition has grown significantly. However, ...
Abstract: Communicating with hearing-impaired people is difficult. Meeting society's requirements requires developing systems that can recognize indications and notify people. Deaf-mute people now ...
Abstract: The lack of labeled data and model generalization abilities have historically represented major obstacles for Human Activity Recognition (HAR). Few-Shot Learning (FSL) addresses both of ...
Abstract: Fine-grained entity recognition (FGER) attracts increasing attention in information extraction and many other natural language understanding applications. However, it is a quite challenging ...
Abstract: People with speech and hearing impairments primarily rely on sign language for communication. However, most hearing individuals are unfamiliar with sign language, making daily interactions ...
Abstract: In an era of increasing urbanization and growing traffic difficulties, this research project presents a classification model tailored for Multi-Class Traffic Management. Our goal with ...
Abstract: We present a novel Automatic Speech Recognition (ASR) dataset for the Oromo language, a widely spoken language in Ethiopia and neighboring regions. The dataset was collected through a ...
Abstract: This research provides a smoother way for detecting real-time sign language using adaptive ensemble learning. Still, 72 million people around the world rely on sign language recognition as ...
A deaf dog who was abandoned and spent 1,452 days in a shelter has finally found his forever home. "Neville has settled in so well with his new family and is loving life in his forever home. He has a ...
(CNN) — The Pentagon is telling beat reporters to sign restrictive new rules by Tuesday or surrender their press passes by Wednesday. Virtually every news outlet is rejecting the ultimatum and saying ...
Abstract: Pose-based isolated sign language recognition (ISLR) demonstrates strong resilience to background noise and maintains computational efficiency. Existing methods typically use raw pose data, ...
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