May 1, 2021 · In order to resolve the challenges of dynamic ASL recognition, a more advanced successor of the Convolutional Neural Networks (CNNs) called 3-D CNNs is employed, which …

This work proposes a novel computer vision approach for recognizing American Sign Language (ASL) gestures, utilizing OpenCV for image capture and manipulation, and MediaPipe for …

This project implements a system that uses a Convolutional Neural Network (CNN) to recognize American Sign Language (ASL) hand gestures, specifically the ASL alphabet. The model is …

In this notebook, I trained a convolutional neural network to classify images of American Sign Language (ASL) letters. After loading, examining, and preprocessing the data, I trained the …

project focuses on American Sign Language (ASL) char-acter detection using CNNs. The input to our algorithm is static images of ASL character signs, with variation in the dataset coming from …

are compared to Pose-GRU, Pose-TGCN, VGG-GRU, and I3D. The model achieved top-1. accuracy of 51.51%, outperforming Pose-GRU and VGG-GRU. Fur-thermore, the top-5 …

Oct 7, 2023 · This article will provide a high-level overview of a project I’ve been working on — an ASL sign detection application using a Convolutional Neural Network (CNN). It will cover the …

ASL detection using CNNs in a range of applications, such as accessibility tools, education, virtual and augmented reality, and human-computer interaction. By illustrating these. lives of deaf …

Jul 1, 2021 · In order to resolve the challenges of dynamic ASL recognition, a more advanced successor of the Convolutional Neural Networks (CNNs) called 3-D CNNs is employed, which …

Real-time sign language recognition solution employing a 3D CNN-LSTM machine learning architecture to accurately identify and translate gestures into textual format. This system is …