One-Stage-TFS: Thai One-Stage Fingerspelling Dataset

The dataset supports a wide range of applications in computer science, including deep learning, computer vision, and pattern recognition, thereby encouraging further innovation and exploration in these fields. Keywords: One-stage fingerspelling; Fingerspelling recognition; Hand detection; Hand gesture recognition; Deep learning; Computer vision Subject: Computer Science Specific subject area: Fingerspelling recognition is a crucial component of hand gesture recognition frameworks.

The Thai One-Stage Fingerspelling Dataset includes images and annotated files that indicate the location of the hand within the images. This dataset is designed to support the detection of hand gestures and the recognition of fingerspelling. Additionally, it is relevant to various fields, including deep learning, computer vision, pattern recognition, and computer science applications.

Type of data: Image (JPG format) and Raw (XML format) Data collection: The Thai One-Stage Fingerspelling (One-Stage-TFS) Dataset provides fingerspelling in the Thai language, focusing exclusively on one-stage consonants. The dataset was collected between July and December 2021 by undergraduate students at Rajabhat Maha Sarakham University, Thailand. The contributors included students from the Special Education Department with experience in Thai sign language and students from other departments without experience.

Data source location: Institution: Rajabhat Maha Sarakham University Province: Mahasarakham Country: Thailand Related research article: S. Lata, O. Surinta, An end-to-end Thai fingerspelling recognition framework with deep convolutional neural networks, ICIC Express Letters 16 (2022) 529–536. doi.org/10.24507/icicel.16.05.5529