A video dataset on agricultural words in Indian sign language

The dataset includes the videos of the dynamic hand gestures for the agricultural words from Indian sign language (ISL). This dataset is used in a work on the recognition of hand gestures for the Indian sign language (ISL) words commonly used by deaf farmers. A hybrid deep learning model with convolutional long short term memory (LSTM) network has been exploited for gesture classification. The model has attained an average classification accuracy of 76.21% on the proposed dataset of ISL words from the agricultural domain. The work is published in the journal Expert Systems with Applications https://www.sciencedirect.com/science/article/abs/pii/S0957417421010009.

本数据集收录了印度手语（Indian Sign Language，ISL）中农业相关词汇对应的动态手部手势视频。该数据集被应用于一项面向听障农民常用印度手语（ISL）词汇的手部手势识别研究工作。研究采用了一种融合卷积长短期记忆（Convolutional Long Short-Term Memory，LSTM）网络的混合深度学习模型来完成手势分类任务。该模型在本研究构建的农业领域印度手语词汇数据集上，取得了76.21%的平均分类准确率。该项研究成果已发表于期刊《Expert Systems with Applications》，原文链接为：https://www.sciencedirect.com/science/article/abs/pii/S0957417421010009。