3 accepted papers
Facial Emotion Analysis (FEA) extends traditional facial emotion recognition by incorporating explainable, fine-grained reasoning. The task integrates three subtasks—emotion recognition, facial Action Unit (AU) recognition, and AU-based emotion reasoning—to jointly model affective states. While re
Deep learning has demonstrated promising results over traditional hand-crafted methods for automatic modulation classification (AMC), which plays a critical role as an intermediate step between signal detection and modulation. However, acquiring large-scale labeled data remains challenging, as both…
In this paper, a new method to classify the animal sound signals that are overlapped in time-frequency domain based on sparse representation is proposed. In order to obtain a discriminant sparse representation of overlapped animal sound signals, a novel dictionary atom discriminant factor is introdu…