Image classification automatic annotation method based on unknown pre-training annotation data
A technology for automatically labeling and labeling data, applied in the field of deep learning and computer vision, can solve the problems of long training time, inconvenient storage and transmission, and large space occupied by pre-training data sets, so as to reduce storage and transmission costs and automatically label The effect of improving accuracy and saving labeling costs
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[0054]The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention, but not to limit the present invention.
[0055] like figure 1 , 2 As shown, the present invention discloses an automatic labeling method for image classification based on pre-training labeling data agnostic, comprising the following steps:
[0056] Step 1: Obtain the image to be labeled X i (i=1, 2...N), the number is N. Offline collection of pre-trained image classification tasks corresponding to performance SOTA image classification models. Specifically, refer to the following but not limited to the following model selections: VGG, ResNet, DenseNet, Inception.
[0057] As an optional implementation manner, a pre-trained image classification model M is obtained, and the label space C corresponding to M inc...
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