Image classification through label progression
AssigneeApple Inc.
InventorsHessam Bagherinezhad, Maxwell Horton, Mohammad Rastegari, Ali Farhadi
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Abstract
Systems and methods are disclosed for training neural networks using labels for training data that are dynamically refined using neural networks and using these trained neural networks to perform detection and/or classification of one or more objects appearing in an image. Particular embodiments may generate a set of crops of images from a corpus of images, then apply a first neural network to the set of crops to obtain a set of respective outputs. A second neural network may then be trained using the set of crops as training examples. The set of respective outputs may be applied as labels for the set of crops.
Claims20
A method comprising:
- obtaining a first image from an image sensor;
- applying, by a computing device to the first image, a neural network that has been trained using training data that includes a set of crops of an image and a set of respective outputs from another neural network that are applied as labels for the set of crops;
- modifying, by the computing device, at least one parameter for operating the image sensor based on an output of the neural network;
- and
- obtaining, by the computing device, a second image with the image sensor using the at least one modified parameter.
A system, comprising:
- a processing apparatus configured to:
- obtain a first image from an image sensor;
- apply, to the first image, a neural network that has been trained using training data that includes a set of crops of an image and a set of respective outputs from another neural network that are applied as labels for the set of crops;
- modify at least one parameter for operating the image sensor based on an output of the neural network;
- and
- obtain a second image with the image sensor using the at least one modified parameter.
A non-transitory machine-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
- obtaining, by a computing device, a first image from an image sensor;
- applying, by the computing device to the first image, a neural network that has been trained using training data that includes a set of crops of an image and a set of respective outputs from another neural network that are applied as labels for the set of crops;
- modifying, by the computing device, at least one parameter for operating the image sensor based on an output of the neural network;
- and
- obtaining, by the computing device, a second image with the image sensor using the at least one modified parameter.
Dependencies are inferred from the claim text.