Neural network training method, device, equipment and storage medium
A neural network training and network technology, applied in the field of deep learning, can solve the problem of low network accuracy of students
Active Publication Date: 2021-07-09
MEGVII BEIJINGTECH CO LTD
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[0005] Based on this, it is necessary to provide a neural network training method, device, equipment and storage medium for the problem of low accuracy of the student network
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[0048] The neural network training method, device, equipment and storage medium provided by this application are aimed at solving the problem of low accuracy of the student network. The technical solution of the present application and how the technical solution of the present application solves the above technical problems will be described in detail below through embodiments and in conjunction with the accompanying drawings. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.
[0049] The neural network training method provided in this embodiment can be applicable to such asfigure 1 shown in the application environment. The neural network training method described above is applied to the neural network training terminal. Neural network training terminals can be, but are not limited to, various personal computers, laptops, smart phones, tablets, and portable wearable device...
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The present invention relates to a neural network training method, device, equipment and storage medium. The terminal obtains the first foreground information and the second foreground information of the picture to be trained through a preset extraction method, and uses the preset The encoder obtains the low-dimensional feature map of the teacher network. At the same time, according to the second foreground information, the encoder is used to obtain the low-dimensional feature map of the student network, and then according to the low-dimensional feature map of the teacher network and the low-dimensional feature map of the student network, the supervision of the student network is determined. Loss function, and according to the supervised loss function, and the preset self-learning loss function, train the student network, and the self-learning loss function is used to train the student network according to the real data label. In the loss function of the training student network, the supervised loss function that only acts on the foreground information and the self-learning loss function obtained according to the real data label are used at the same time, so the loss function of the student network is more accurate and the accuracy of the student network is improved.
Description
technical field [0001] The present invention relates to the technical field of deep learning, in particular to a neural network training method, device, equipment and storage medium. Background technique [0002] Convolutional neural networks are usually used for data processing in computer vision tasks. Generally speaking, a network with higher accuracy requires more calculations, and is not suitable for small devices or mobile devices, etc. With the help of a large network, a small network is trained so that the small network also has relatively high accuracy in vision tasks. In this case, the large network is called the teacher network, and the small network is called the student network. During the training process, the student network not only obtains information from the real labels, but also obtains information from the teacher network. The accuracy of the student network trained in this way is often higher than that of the student network trained only with real lab...
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IPC IPC(8): G06N3/04G06N3/08G06K9/62
CPCG06N3/084G06N3/045G06F18/24
Inventor 郭义袁野王剑锋俞刚
Owner MEGVII BEIJINGTECH CO LTD