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Our model is generated by applying the Random Forest Classifier Algorithm, which is then integrated with Mediapipe to analyze the hand gesture and recognize the alphabet. Thus, when presented with a ...
Technological advancements play a significant role in the integration of deaf and mute individuals into society. Therefore, improvements in sign language recognition systems are of great importance.
This project is designed to recognize American Sign Language (ASL) alphabet gestures in real-time using computer vision and machine learning. By utilizing OpenCV for webcam integration, MediaPipe for ...
This paper introduces a Convolutional Neural Network (CNN) model for Arabic Sign Language (AASL) recognition, using the AASL dataset. Recognizing the fundamental importance of communication for the ...
To solve the problems of low recognition accuracy and poor robustness of existing sign language letters recognition models in scenes such as complex background interference and overlapping hands, in ...
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Computer Vision-Based Recognition of American Sign Language - MSNResearchers from Florida Atlantic University have carried out a first-of-its-kind study on computer vision-based recognition of American Sign Language alphabet motions. Sign language serves as a ...
Transfer learning with YOLOV8 for real-time recognition system of American Sign Language Alphabet. Franklin Open , 2024; 8: 100165 DOI: 10.1016/j.fraope.2024.100165 Cite This Page : ...
The study employed a two-step methodology using YOLOv8 and MediaPipe for real-time recognition of American Sign Language (ASL) alphabet gestures. Initially, YOLOv8 was used to detect and localize hand ...
Creative studio Hello Monday has created an app that teaches hand positions in real-time to make it easier for people to learn the sign language alphabet.
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