Sign language functions as the fundamental communication method through which deaf along with hard-of-hearing individuals establish effective interactions with those without hearing disabilities. Sign language users create isolated communication areas that minimize the numerous Potential contacts that exist between themselves and users of other communication methods. Real-Time Sign Language Recognition operates as an interpreter without sign language skills to understand and value the language they normally cannot use. An exact detection of gestures occurs through deep learning integration with computer vision algorithms within the system. As an accessibility service and communication network Signing allows users with sign language to contact non-users of the platform.

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Real-Time Sign Language Recognition a Model Comparison Using MobileNetV2, VGG16, and FNN

  • Madira Sai Rishitha,
  • M. Kamala,
  • Ch. Mukunda Sri Hasini,
  • Dasi Rashmika

摘要

Sign language functions as the fundamental communication method through which deaf along with hard-of-hearing individuals establish effective interactions with those without hearing disabilities. Sign language users create isolated communication areas that minimize the numerous Potential contacts that exist between themselves and users of other communication methods. Real-Time Sign Language Recognition operates as an interpreter without sign language skills to understand and value the language they normally cannot use. An exact detection of gestures occurs through deep learning integration with computer vision algorithms within the system. As an accessibility service and communication network Signing allows users with sign language to contact non-users of the platform.