The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Mar. 31, 2020
Filed:
Dec. 13, 2017
Microsoft Technology Licensing, Llc, Redmond, WA (US);
Arun Sacheti, Sammamish, WA (US);
FNU Yokesh Kumar, Kirkland, WA (US);
Saurajit Mukherjee, Kirkland, WA (US);
Nikesh Srivastava, Redmond, WA (US);
Yan Wang, Mercer Island, WA (US);
Kuang-Huei Lee, Bellevue, WA (US);
Surendra Ulabala, Bothell, WA (US);
Microsoft Technology Licensing, LLC, Redmond, WA (US);
Abstract
Non-limiting examples described herein relate to ensemble model processing for image recognition that improves precision and recall for image recognition processing as compared with existing solutions. An exemplary ensemble model is configured enhance image recognition processing through aggregate data modeling processing that evaluates image recognition prediction results obtained through processing that comprises: nearest neighbor visual search analysis, categorical image classification analysis and/or categorical instance retrieval analysis. An exemplary ensemble model is scalable, where new segments/categories can be bootstrapped to build deeper learning models and achieve high precision image recognition, while the cost of implementation (including from a bandwidth and resource standpoint) is lower than what is currently available across the industry today. Processing described herein, including implementation of an exemplary ensemble data model, may be exposed as a web service that is standalone or integrated within other applications/services to enhance processing efficiency and productivity applications/services such as productivity applications/services.