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Learning to Adapt to Domain Shifts with Few-shot Samples in Anomalous
  Sound Detection

Learning to Adapt to Domain Shifts with Few-shot Samples in Anomalous Sound Detection

5 April 2022
Bingqing Chen
Luca Bondi
Samarjit Das
ArXivPDFHTML

Papers citing "Learning to Adapt to Domain Shifts with Few-shot Samples in Anomalous Sound Detection"

5 / 5 papers shown
Title
Handling Domain Shifts for Anomalous Sound Detection: A Review of DCASE-Related Work
Kevin Wilkinghoff
Takuya Fujimura
Keisuke Imoto
Jonathan Le Roux
Zheng-Hua Tan
T. Toda
45
0
0
13 Mar 2025
Anomalous Sound Detection using Audio Representation with Machine ID
  based Contrastive Learning Pretraining
Anomalous Sound Detection using Audio Representation with Machine ID based Contrastive Learning Pretraining
Jian Guan
Feiyang Xiao
Youde Liu
Qiaoxi Zhu
Wenwu Wang
8
10
0
07 Apr 2023
Zero-Shot Anomaly Detection via Batch Normalization
Zero-Shot Anomaly Detection via Batch Normalization
Aodong Li
Chen Qiu
Marius Kloft
Padhraic Smyth
Maja R. Rudolph
Stephan Mandt
12
0
0
15 Feb 2023
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness
  of MAML
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Aniruddh Raghu
M. Raghu
Samy Bengio
Oriol Vinyals
170
634
0
19 Sep 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
237
11,568
0
09 Mar 2017
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