JP7468540B2 - 学習システム、学習装置、および学習方法 - Google Patents

学習システム、学習装置、および学習方法 Download PDF

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JP7468540B2
JP7468540B2 JP2021550747A JP2021550747A JP7468540B2 JP 7468540 B2 JP7468540 B2 JP 7468540B2 JP 2021550747 A JP2021550747 A JP 2021550747A JP 2021550747 A JP2021550747 A JP 2021550747A JP 7468540 B2 JP7468540 B2 JP 7468540B2
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亮 高本
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NEC Corp
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    • G06—COMPUTING OR CALCULATING; COUNTING
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    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
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JP2021550747A 2019-09-30 2019-09-30 学習システム、学習装置、および学習方法 Active JP7468540B2 (ja)

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CN114981820A (zh) * 2019-12-20 2022-08-30 谷歌有限责任公司 用于在边缘设备上评估和选择性蒸馏机器学习模型的系统和方法
WO2021182748A1 (ko) * 2020-03-10 2021-09-16 삼성전자주식회사 전자 장치 및 그 제어 방법
US12210585B2 (en) * 2021-03-10 2025-01-28 Qualcomm Incorporated Efficient test-time adaptation for improved temporal consistency in video processing
CN113283578B (zh) * 2021-04-14 2024-07-23 南京大学 一种基于标记风险控制的数据去噪方法
CN117751380A (zh) * 2021-08-05 2024-03-22 富士通株式会社 生成方法、信息处理装置以及生成程序
JP7683426B2 (ja) * 2021-08-31 2025-05-27 株式会社Ｊｖｃケンウッド 画像処理装置、画像処理方法、および画像処理プログラム
WO2023048437A1 (ko) * 2021-09-25 2023-03-30 주식회사 메디컬에이아이 의료 데이터를 기반으로 하는 딥러닝 모델의 학습 및 추론 방법, 프로그램 및 장치
US11853392B2 (en) * 2021-11-30 2023-12-26 International Business Machines Corporation Providing reduced training data for training a machine learning model
JP7840834B2 (ja) * 2022-12-01 2026-04-06 株式会社東芝 学習装置、方法、プログラム及び推論装置
CN116030323B (zh) * 2023-03-27 2023-08-29 阿里巴巴（中国）有限公司 图像处理方法以及装置

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US20170132528A1 (en) * 2015-11-06 2017-05-11 Microsoft Technology Licensing, Llc Joint model training

Non-Patent Citations (4)

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Title
ROMERO, Adriana ほか，FitNets: Hints for Thin Deep Nets，arXiv[online]，2015年03月27日，pp.1-13，[retrieved on 2019.12.10], Retrieved from the Internet: <URL: https://arxiv.org/pdf/1412.6550v4>
WANG, Zihan ほか，CrossWeigh: Training Named Entity Tagger from Imperfect Annotations，arXiv[online]，2019年09月03日，[retrieved on 2023.10.30], Retrieved from the Internet: <URL: https://arxiv.org/pdf/1909.01441.pdf>
yuzupepper，論文メモ：Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach，Qiita[online]，2017年08月20日，[retrieved on 2019.12.10], Retrieved from the Internet: <URL: https://qiita.com/yuzupepper/items/b15
ラベルの付け間違いが分かる！？，The Labellio Blog[online]，2019年07月04日，[retrieved on 2019.12.10], Retrieved from the Internet: <URL: https://www.kccs.co.jp/labellio_blog_j

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