143 citations · 511 across the 26 of their papers we have counts for
3 papers · 1 filter
AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation
Masataka Yamaguchi, Yuma Koizumi, Noboru Harada
We tackle unsupervised anomaly detection (UAD), a problem of detecting data that significantly differ from normal data. UAD is typically solved by using density estimation. Recentl…
Trainable Adaptive Window Switching for Speech Enhancement
Yuma Koizumi, Noboru Harada, Yoichi Haneda
This study proposes a trainable adaptive window switching (AWS) method and apply it to a deep-neural-network (DNN) for speech enhancement in the modified discrete cosine transform…
Unsupervised Detection of Anomalous Sound based on Deep Learning and the Neyman-Pearson Lemma
Yuma Koizumi, Shoichiro Saito, Hisashi Uematsum Yuta Kawachi +1
This paper proposes a novel optimization principle and its implementation for unsupervised anomaly detection in sound (ADS) using an autoencoder (AE). The goal of unsupervised-ADS…