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DIFF Subgroup
G06V 10/77

Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation

Introduced: January 2022

Full Title

Full titles differ between systems:

IPC:

Arrangements for image or video recognition or understanding > using pattern recognition or machine learning > Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation

CPC:

Arrangements for image or video recognition or understanding (character recognition in images or video G06V30/10) > using pattern recognition or machine learning (optical pattern recognition or electronic computations therefor G06V10/88) > Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation

Additional Content IPC

BSS blind source separation eigenface eigenfaces name given to a set of eigenvectors obtained by principal component analysis when used in face recognition. ICA independent component analysis LDA linear discriminant analysis MDS multidimensional scaling PCA principal component analysis SOM self-organising map

Of 7 combined children, 6 exist in both systems.

1 codes are CPC-only extensions.

1 shared codes have differing titles between IPC and CPC.

IPC defines codes here since 2022.

Child Classifications

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  • G06V 10/771 Feature selection, e.g. selecting representative features from a multi-dimensional feature space since 2022 IPC+CPC Available in IPC and CPC
  • G06V 10/7715 CPC only CPC only
  • G06V 10/772 Determining representative reference patterns, e.g. averaging or distorting patterns; Generating dictionaries since 2022 IPC+CPC Available in IPC and CPC
  • G06V 10/776 Validation; Performance evaluation since 2022 IPC+CPC Available in IPC and CPC

Top Applicants

Top Applicants (IPC)

Class G06,2013–2023, worldwide · Source: EPO PATSTAT

  1. SAMSUNG ELECTRONICS COMPANY KR 66,669
  2. IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,313
  3. MICROSOFT TECHNOLOGY LICENSING US 41,918
  4. GOOGLE US 32,969
  5. SGCC(STATE GRID CORPORATION OF CHINA) 30,822
  6. INTEL CORPORATION US 30,010
  7. TENCENT TECHNOLOGY (SHENZHEN) COMPANY 28,235
  8. HUAWEI TECHNOLOGIES COMPANY CN 26,079
  9. APPLE US 21,891
  10. HUAWEI TECHNOLOGIES COMPANY 20,505

Top Applicants (CPC)

Class G06,2013–2023, worldwide · Source: EPO PATSTAT

  1. SAMSUNG ELECTRONICS COMPANY KR 76,952
  2. IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,841
  3. MICROSOFT TECHNOLOGY LICENSING US 44,778
  4. GOOGLE US 35,735
  5. INTEL CORPORATION US 32,087
  6. HUAWEI TECHNOLOGIES COMPANY CN 30,572
  7. TENCENT TECHNOLOGY (SHENZHEN) COMPANY 25,023
  8. APPLE US 23,482
  9. SGCC(STATE GRID CORPORATION OF CHINA) 22,548
  10. HUAWEI TECHNOLOGIES COMPANY 20,917