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US 9,852,492 B2Granted
Face detection
AssigneeYahoo Holdings, Inc.
InventorsMohammad Saberian, Sachin Sudhakar Farfade, Jia Li
Life of this patent
Estimating the term…
Abstract
Briefly, embodiments of methods and/or systems of detecting and image of a human face in a digital image are disclosed. For one embodiment, as an example, parameters of a neural network may be developed to generate object labels for digital images. The developed parameters may be refined by a neural network to generate signal sample value levels corresponding to probability that a human face may be depicted at a localized region of a digital image.
Claims20
A method, comprising:
- training parameters of a convolutional neural network (CNN) to label everyday objects;
- and
- refining the parameters of the CNN, trained to label the everyday objects, to perform multi-aspect facial detection with respect to one or more images, the CNN being modified to exclude fully-connected layers.
An apparatus, comprising:
- one or more processors to:
- train parameters of a convolutional neural network (CNN) to label everyday objects;
- and
- refine parameters of the CNN, trained to label the everyday objects, to perform multi-aspect facial detection with respect to one or more images, the CNN modified to exclude fully-connected layers.
1 more element
An apparatus comprising:
- means for training parameters of a convolutional neural network (CNN) to label everyday objects;
- and
- means for refining the parameters of the CNN, trained to label the everyday objects, to perform multi-aspect facial detection, wherein the means for refining comprises means for modifying the CNN to exclude fully-connected layers.
Dependencies are inferred from the claim text.