14 citations · 15 across the 7 of their papers we have counts for
7 papers
DualMark: Identifying Model and Training Data Origins in Generated Audio
Xuefeng Yang, Jian Guan, Feiyang Xiao +5
Existing watermarking methods for audio generative models only enable model-level attribution, allowing the identification of the originating generation model, but are unable to tr…
Aneumo: A Large-Scale Multimodal Aneurysm Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
Xigui Li, Yuanye Zhou, Feiyang Xiao +16
Intracranial aneurysms (IAs) are serious cerebrovascular lesions found in approximately 5\% of the general population. Their rupture may lead to high mortality. Current methods for…
Transformer-based Autoencoder with ID Constraint for Unsupervised Anomalous Sound Detection
Jian Guan, Youde Liu, Qiuqiang Kong +4
Unsupervised anomalous sound detection (ASD) aims to detect unknown anomalous sounds of devices when only normal sound data is available. The autoencoder (AE) and self-supervised l…
Synth-AC: Enhancing Audio Captioning with Synthetic Supervision
Feiyang Xiao, Qiaoxi Zhu, Jian Guan +4
Data-driven approaches hold promise for audio captioning. However, the development of audio captioning methods can be biased due to the limited availability and quality of text-aud…
Anomalous Sound Detection Using Self-Attention-Based Frequency Pattern Analysis of Machine Sounds
Hejing Zhang, Jian Guan, Qiaoxi Zhu +2
Different machines can exhibit diverse frequency patterns in their emitted sound. This feature has been recently explored in anomaly sound detection and reached state-of-the-art pe…
Anomalous Sound Detection using Audio Representation with Machine ID based Contrastive Learning Pretraining
Jian Guan, Feiyang Xiao, Youde Liu +2
Existing contrastive learning methods for anomalous sound detection refine the audio representation of each audio sample by using the contrast between the samples' augmentations (e…