Systems and methods for machine learning enhanced by human measurements
US-9792532-B2 · Oct 17, 2017 · US
Systems and methods for machine learning enhanced by human measurements
US10062011B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10062011-B2 |
| Application number | US-201715702809-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 13, 2017 |
| Priority date | Jun 28, 2013 |
| Publication date | Aug 28, 2018 |
| Grant date | Aug 28, 2018 |
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Abstract
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In various embodiments, training objects are classified by human annotators, psychometric data characterizing the annotation of the training objects is acquired, a human-weighted loss function based at least in part on the classification data and the psychometric data is computationally derived, and one or more features of a query object are computationally classified based at least in part on the human-weighted loss function.
First claim
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What is claimed is: 1. A computer-implemented method for data classification and identification utilizing a human-weighted loss function produced by (i) providing, over a computer network, data corresponding to a plurality of training objects to a plurality of training devices each associated with one of a plurality of human annotators, each of the training objects comprising features for classification, (ii) displaying the training objects on a display of each of the training devi…
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Physics · mapped topic
- G06F18/2178Primary
Physics · mapped topic
- G06K9/6263Primary
Physics · mapped topic
Physics · mapped topic
Physics · mapped topic
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- What does patent US10062011B2 cover?
- In various embodiments, training objects are classified by human annotators, psychometric data characterizing the annotation of the training objects is acquired, a human-weighted loss function based at least in part on the classification data and the psychometric data is computationally derived, and one or more features of a query object are computationally classified based at least in part on …
- Who is the assignee on this patent?
- Cox David, Scheirer Walter, Anthony Samuel, and 2 more
- What technology area does this patent fall under?
- Primary CPC classification G06F18/2178. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Tue Aug 28 2018 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 3 related publications on this page (citations in our corpus or others sharing the same primary CPC).