This study introduced a proposed system that offered SLR in real-time for some gestures from the American sign language (ASL), by using one of the most suitable deep learning-based...

In this paper, a Convolutional Neural Network (CNN) based Hybrid Single Stage Recognition (Hybrid-SSR) framework is proposed for real-time hand gesture recognition. The time-efficient Enhanced...

Sign language recognition (SLR) is a bridge linking the hearing impaired and the general public. Some SLR methods using wearable data gloves are not portable enough to provide daily...

The Realtime Sign Language Detection Using LSTM Model is a deep learning-based project that aims to recognize and interpret sign language gestures in real-time. It utilizes a Long Short-Term Memory (LSTM) neural network architecture to learn and classify sign language gestures captured from a video feed.

Apr 9, 2025 · Sign Language Gesture Recognition From Video Sequences Using RNN And CNN. Simple sign language alphabet recognizer using Python, openCV and tensorflow for training Inception model (CNN classifier). isolated & continuous sign language recognition using CNN+LSTM/3D CNN/GCN/Encoder-Decoder.

Sign Language Detection is a project aimed at recognizing and interpreting hand gestures from sign language. This end-to-end solution employs the YOLOv5 object detection model to identify sign language phrases such as "Hello," "I love you," "Yes," "No," and "Please."

image and predict the gestures. This paper shows the sign language recognition of 26 alphabets and 0-9 digits hand gestures of American Sign Language. The proposed system contains modules such as pre-processing and feature extraction, training …

Apr 9, 2025 · Building an automated system to recognize sign language can significantly improve accessibility and inclusivity. In this article we will develop a Sign Language Recognition System using TensorFlow and Convolutional Neural Networks (CNNs) .

However, not everyone knows sign language, which hinders communication. To solve this, an automated Sign Language Recognition system was created using TensorFlow object detection API. The Indian Sign Language alphabet dataset was used to train this system, which translates sign language into spoken words. The model uses

It maps out the flow of information for any process or system, how data is processed in terms of inputs and outputs. It uses defined symbols like rectangles, circles and arrows to show data inputs, outputs, storage points and the routes between each destination. They can be used to analyse an existing system or model of a new one.