10 citations · 14 across the 8 of their papers we have counts for
9 papers
Relative Mismatch: Local-Reference Calibration of Feature-Space Flows for Anomalous Sound Detection
Anbai Jiang, Xinhu Zheng, Lvxin Xu +6
Anomalous sound detection (ASD) has long been dominated by k-nearest-neighbor (KNN) based detectors, which essentially perform implicit likelihood estimation over normal samples. I…
Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection
Bing Han, Anbai Jiang, Xinhu Zheng +4
Machine anomalous sound detection (ASD) is a valuable technique across various applications. However, its generalization performance is often limited due to challenges in data coll…
FISHER: A Foundation Model for Multi-Modal Industrial Signal Comprehensive Representation
Pingyi Fan, Anbai Jiang, Shuwei Zhang +9
Industrial signal analysis is hindered by severe data heterogeneity, which we characterize as the M5 problem. Existing solutions rely on specialized models that lack robustness and…
Data-Efficient Low-Complexity Acoustic Scene Classification via Distilling and Progressive Pruning
Bing Han, Wen Huang, Zhengyang Chen +7
The goal of the acoustic scene classification (ASC) task is to classify recordings into one of the predefined acoustic scene classes. However, in real-world scenarios, ASC systems…
Improving Anomalous Sound Detection via Low-Rank Adaptation Fine-Tuning of Pre-Trained Audio Models
Xinhu Zheng, Anbai Jiang, Bing Han +4
Anomalous Sound Detection (ASD) has gained significant interest through the application of various Artificial Intelligence (AI) technologies in industrial settings. Though possessi…
CoopASD: Cooperative Machine Anomalous Sound Detection with Privacy Concerns
Anbai Jiang, Yuchen Shi, Pingyi Fan +2
Machine anomalous sound detection (ASD) has emerged as one of the most promising applications in the Industrial Internet of Things (IIoT) due to its unprecedented efficacy in mitig…
AnoPatch: Towards Better Consistency in Machine Anomalous Sound Detection
Anbai Jiang, Bing Han, Zhiqiang Lv +6
Large pre-trained models have demonstrated dominant performances in multiple areas, where the consistency between pre-training and fine-tuning is the key to success. However, few w…
Unsupervised Anomaly Detection and Localization of Machine Audio: A GAN-based Approach
Anbai Jiang, Wei-Qiang Zhang, Yufeng Deng +2
Automatic detection of machine anomaly remains challenging for machine learning. We believe the capability of generative adversarial network (GAN) suits the need of machine audio a…
Soft Compression for Lossless Image Coding
Gangtao Xin, Pingyi Fan
Soft compression is a lossless image compression method, which is committed to eliminating coding redundancy and spatial redundancy at the same time by adopting locations and shape…