Invention Grant
- Patent Title: Methods and apparatus for conditional classifier chaining in a constrained machine learning environment
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Application No.: US16226131Application Date: 2018-12-19
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Publication No.: US10863329B2Publication Date: 2020-12-08
- Inventor: Keith A. Ellis , Giovani Estrada , David Coates , Michael Nolan
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Hanley, Flight & Zimmerman, LLC
- Main IPC: H04L29/08
- IPC: H04L29/08 ; H04W4/38 ; G06F13/16 ; G06K9/62 ; G06N20/00 ; H04L12/24

Abstract:
Methods, apparatus, systems, and articles of manufacture for conditional classifier chaining in a constrained machine learning environment are disclosed. An example apparatus includes a classification controller to select a first model to be utilized to classify a first feature identified from sensor data. A memory controller is to copy the first model to a memory. A machine learning processor is to apply the first model to the first feature to create a first classification output, the first classification output indicating an identified class. The classification controller is to, in response to a determination that the first classification output identifies a second model to be used for classification, instruct the memory controller to load the second model into the memory. The machine learning processor is to apply the second model to the second feature to create a second classification output.
Public/Granted literature
- US20190124488A1 METHODS AND APPARATUS FOR CONDITIONAL CLASSIFIER CHAINING IN A CONSTRAINED MACHINE LEARNING ENVIRONMENT Public/Granted day:2019-04-25
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