Information processing apparatus for training neural network for recognition task and method thereof
AssigneeCanon Kabushiki Kaisha
InventorTakayuki Saruta
Life of this patent
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Abstract
An apparatus includes a multitask setting unit configured to set a plurality of recognition tasks for which a multilayer neural network is trained, a neural network (NN) training unit configured to train the multilayer NN for the set plurality of recognition tasks, an NN evaluation unit configured to evaluate a training result of the multilayer NN, and a training parameter setting unit configured to set a training parameter in training the multilayer NN for the plurality of recognition tasks, based on a result of evaluation by the NN evaluation unit.
Claims20
An apparatus comprising:
- a processor;
- and
- a memory coupled to the processor storing instructions that, when executed by the processor, cause the processor to function as:
- a task setting unit configured to set a plurality of recognition tasks for which a neural network or a classifier is trained, wherein the plurality of recognition tasks is to recognize targets different from each other;
- a training unit configured to train the neural network or the classifier for the plurality of tasks based on training data and a teaching value for the plurality of recognition tasks;
- an evaluation unit configured to evaluate a training result of the neural network or of the classifier;
- and
- a parameter setting unit configured to set a training parameter including weight assigned to errors in the plurality of recognition tasks in training the neural network or the classifier for the plurality of recognition tasks, based on a result of evaluation by the evaluation unit,
- wherein the training unit performs second training on the neural network or the classifier according to the training parameter set by the parameter setting unit based on the result of evaluation of first training by the evaluation unit.
A method comprising:
- setting a plurality of recognition tasks for which a neural network or a classifier is trained, wherein the plurality of recognition tasks is to recognize targets different from each other;
- training the neural network or the classifier for the plurality of recognition tasks based on training data and a teaching value for the plurality of recognition tasks;
- evaluating a training result of the neural network or of the classifier;
- setting a training parameter including weight assigned to errors in the plurality of recognition tasks in training the neural network or the classifier for the plurality of recognition tasks, based on a result of the evaluating;
- and
- performing second training on the neural network or the classifier according to the training parameter set by the setting based on the result of evaluation of first training by the evaluating.
A non-transitory computer-readable storage medium storing a program for causing a computer to perform:
- setting a plurality of recognition tasks for which a neural network or a classifier is trained, wherein the plurality of recognition tasks is to recognize targets different from each other;
- training the neural network or the classifier for the plurality of recognition tasks based on training data and a teaching value for the plurality of recognition tasks;
- evaluating a training result of the neural network or of the classifier;
- and
- setting a training parameter including weight assigned to errors in the plurality of recognition tasks in training the neural network or the classifier for the plurality of recognition tasks, based on a result of the evaluating;
- and
- performing second training on the neural network or the classifier according to the training parameter set by the setting based on the result of evaluation of first training by the evaluating.
Dependencies are inferred from the claim text.