3 accepted papers
Existing image-to-image translation methods perform less satisfactorily in the "day-night" domain due to insufficient scene feature study. To address this problem, we propose DNIT, which performs fine-grained handling of features by a nighttime image preprocessing (NIP) module and an edge fusion det…
With the growing significance of non-intrusive speech quality assessment in speech systems, existing methods predominantly rely on neural networks to extract low-order features. Typically, these features undergo a low-dimensional linear transformation, yielding the network’s output. However, the int…
Sound event detection (SED) is an interesting but challenging task due to the scarcity of data and diverse sound events in real life. In this paper, we focus on the semi-supervised SED task, and combine pre-trained model from other field to assist in improving the detection effect. Pre-trained model…