Skip to content
Search Classifications
Search for IPC and CPC classification codes or keywords
DIFF Subgroup
G06V 10/80

Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level (multimodal speaker identification or verification G10L17/10)

Introduced: January 2022

Title

Titles differ between systems:

IPC: Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level

CPC: Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level (multimodal speaker identification or verification G10L17/10)

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 > Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level

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 > Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level (multimodal speaker identification or verification G10L17/10)

Additional Content IPC

Glossary

Dempster-Shafer general framework for reasoning with uncertainty which combines evidence from different sources and arrives at a degree of belief (represented by a mathematical object called belief function) that takes into account all the available evidence.

Limiting references

Multimodal speaker identification or verification

Of 5 combined children, 0 exist in both systems.

5 codes are CPC-only extensions.

Child Classifications

Navigate with arrow keys, Enter to open

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