Shubashree Desikan, the Hindu
The annotated datas can be used by deep-learning frameworks employed in AI to learn the model accurately. Understanding user engagement in online interactions is important in many contexts, with online shopping, advertising, e-learning and healthcare being just a few sectors. Now, IIT Hyderabad has built DAiSEE (Dataset for Affective States in E-Environments), the first multilabel video-classification dataset for recognising boredom, confusion, frustration and engagement. The dataset comprises 9,068 video snippets captured from 112 individuals. For each of these affective states, there are further four levels of labels – very low, low, high and very high. These labels are provided by observing the viewer’s reactions.
June 24, 2018
IIT Hyderabad builds dataset to understand online user-engagement
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