Jun 3, 2022 · Deep learning models, namely, LSTM and GRU (feedback-based learning models), are used to recognize signs from isolated Indian Sign Language (ISL) video frames. The four different sequential combinations of LSTM and GRU (as there are two layers of LSTM and two layers of GRU) were used with our own dataset, IISL2020.

Aug 30, 2023 · We create a real-time American Sign Language detector using the skeleton model, which reliably categorizes continuous signs in sign language in most cases using a deep learning approach. In the second deep learning approach, we create a sign language detector for static signs using YOLOv6.

Sep 18, 2023 · Sign language recognition is essential in hearing-impaired people’s communication. Wearable data gloves and computer vision are partially complementary solutions. However, sign language recognition using a general monocular camera suffers from occlusion and recognition accuracy issues.

Jul 11, 2022 · This research aimed to answer the main research question of how effective deep learning and computer vision models could be in narrowing the gap between people with speech impairments who can only use sign language and the general public who …

Jun 3, 2022 · The paper presents a deep learning-based model that detects and recognizes 16 the words from a person’s gestures. The proposed method and its details are well described, allowing a fast implementation.

This paper aims to address the communication gap between specially abled (deaf) people who can only express themselves through the Indian sign language and those who do not understand it, thereby improving accessibility and communication for sign language users.

Sep 19, 2023 · In this paper, we presented a study employing transfer learning techniques utilizing five deep learning models for the effective classification of hand gestures representing the American sign language (ASL) alphabet.

Mar 28, 2025 · This study presents a real-time American Sign Language (ASL) interpretation system that integrates deep learning with keypoint tracking to enhance accessibility and foster inclusivity. By combining the YOLOv11 model for gesture recognition with MediaPipe for precise hand tracking, the system achieves high accuracy in identifying ASL alphabet ...

Aug 14, 2023 · This study presents a sign language recognition system that is capable of recognizing Arabic Sign Language from recorded RGB videos. To achieve this, two datasets were considered, such as (1) the raw dataset and (2) the face–hand region-based segmented dataset produced from the raw dataset.

Mar 24, 2024 · This study introduces an innovative approach to isolated sign language word recognition using a novel deep learning model that combines the strengths of both residual three-dimensional (R3D) and temporally separated (R(2+1)D) convolutional blocks.