JP7262290B2 - 特徴ベクトルを生成するシステム - Google Patents

特徴ベクトルを生成するシステム Download PDF

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JP7262290B2
JP7262290B2 JP2019085609A JP2019085609A JP7262290B2 JP 7262290 B2 JP7262290 B2 JP 7262290B2 JP 2019085609 A JP2019085609 A JP 2019085609A JP 2019085609 A JP2019085609 A JP 2019085609A JP 7262290 B2 JP7262290 B2 JP 7262290B2
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feature vector
class
sample
anchor
distance
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JP2020181486A5 (enExample
JP2020181486A (ja
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マルティン クリンキグト
モーヒト チャーブラ
敦 廣池
智一 村上
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Hitachi Ltd
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Hitachi Ltd
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Priority to JP2019085609A priority Critical patent/JP7262290B2/ja
Priority to PCT/JP2020/017270 priority patent/WO2020218314A1/ja
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Publication of JP2020181486A5 publication Critical patent/JP2020181486A5/ja
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/55—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/907—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/907—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/908—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Library & Information Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Image Analysis (AREA)
JP2019085609A 2019-04-26 2019-04-26 特徴ベクトルを生成するシステム Active JP7262290B2 (ja)

Priority Applications (2)

Application Number Priority Date Filing Date Title
JP2019085609A JP7262290B2 (ja) 2019-04-26 2019-04-26 特徴ベクトルを生成するシステム
PCT/JP2020/017270 WO2020218314A1 (ja) 2019-04-26 2020-04-21 特徴ベクトルを生成するシステム

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Application Number Priority Date Filing Date Title
JP2019085609A JP7262290B2 (ja) 2019-04-26 2019-04-26 特徴ベクトルを生成するシステム

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JP2020181486A JP2020181486A (ja) 2020-11-05
JP2020181486A5 JP2020181486A5 (enExample) 2021-12-23
JP7262290B2 true JP7262290B2 (ja) 2023-04-21

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WO (1) WO2020218314A1 (enExample)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112949384B (zh) * 2021-01-23 2024-03-08 西北工业大学 一种基于对抗性特征提取的遥感图像场景分类方法
CN113408299B (zh) * 2021-06-30 2022-03-25 北京百度网讯科技有限公司 语义表示模型的训练方法、装置、设备和存储介质
CN114399666B (zh) * 2022-01-18 2025-08-05 深圳市东汇精密机电有限公司 基于小样本识别的细胞分级系统
WO2024079820A1 (ja) * 2022-10-12 2024-04-18 日本電気株式会社 学習装置、学習方法、プログラム、および分類装置

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170228641A1 (en) 2016-02-04 2017-08-10 Nec Laboratories America, Inc. Distance metric learning with n-pair loss
US20190065957A1 (en) 2017-08-30 2019-02-28 Google Inc. Distance Metric Learning Using Proxies

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170228641A1 (en) 2016-02-04 2017-08-10 Nec Laboratories America, Inc. Distance metric learning with n-pair loss
US20190065957A1 (en) 2017-08-30 2019-02-28 Google Inc. Distance Metric Learning Using Proxies

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
NI, Jiazhi et al.，Fine-grained Patient Similarity Measuring using Deep Metric Learning，Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (CIKM)，ACM Digita Library，2017年11月，pp.1189-1198，Internet<URL: https://dl.acm.org/doi/10.1145/3132847.313302>

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WO2020218314A1 (ja) 2020-10-29

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