SignAlphaSet
Published: 10 March 2025| Version 1 | DOI: 10.17632/8fmvr9m98w.1
Contributors:
, , Achyut Kashyap, , , Description
This dataset comprises 26,000 images representing American Sign Language (ASL) hand gestures corresponding to the English alphabet (A-Z). The dataset is organized into 26 folders, each labeled with a corresponding letter, containing multiple image samples to ensure variability in hand positioning, lighting, and individual hand differences. The images capture diverse hand gestures, making the dataset suitable for machine learning applications such as sign language recognition, computer vision, and deep learning-based classification tasks. When evaluated using an LSTM-based model, the dataset achieved high accuracy in sign recognition, demonstrating its effectiveness in sequential gesture learning.
Files
Institutions
Bharati Vidyapeeth Deemed University College of Engineering Pune
Categories
Artificial Intelligence, Computer Vision, Machine Learning, Convolutional Neural Network, Deep Learning