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N. Harada

26 papers hereh-index 242.5k citations114 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author13
  • last author10

Across the 24 of 26 papers where every author was matched, so the position is known.

fields
  • eess.AS20
  • cs.SD3
  • stat.ML2
  • eess.SP1
same name
  • N. Harada — 55 papers, h 23
  • N. Harada — 15 papers, h 6
  • N. Harada — 10 papers, h 4
  • N. Harada — 2 papers, h 2
  • N. Harada — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182023
most citedUnsupervised Detection of Anomalous Sound based on Deep Learning and the Neyman-Pearson Lemma

143 citations · 511 across the 26 of their papers we have counts for

collaborators
Showing 2021Show all

3 papers · 1 filter

eess.AS2021★ 25 cited

ToyADMOS2: Another dataset of miniature-machine operating sounds for anomalous sound detection under domain shift conditions

Noboru Harada, Daisuke Niizumi, Daiki Takeuchi +3

This paper proposes a new large-scale dataset called "ToyADMOS2" for anomaly detection in machine operating sounds (ADMOS). As did for our previous ToyADMOS dataset, we collected a…

eess.AS2021★ 34 cited

Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions

Yohei Kawaguchi, Keisuke Imoto, Yuma Koizumi +6

We present the task description and discussion on the results of the DCASE 2021 Challenge Task 2. In 2020, we organized an unsupervised anomalous sound detection (ASD) task, identi…

eess.AS2021★ 1 cited

BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation

Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi +2

Inspired by the recent progress in self-supervised learning for computer vision that generates supervision using data augmentations, we explore a new general-purpose audio represen…

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