Online learning method and device for deep learning model, equipment and medium

Abstract

The invention is suitable for the technical field of deep learning, and provides an online learning method and device for a deep learning model, equipment and a medium. The online learning method comprises the following steps: performing offline training on the deep learning model into which the suppression signal is introduced; after training, publishing the deep learning model on a line; enabling the received online training image to be subjected to image identification; cutting an unrecognizable online training image through a sliding window; obtaining a corresponding basic feature set; carrying out similarity matching on the obtained basic feature set and a training image set; setting the basic features corresponding to the similarity lower than a similarity threshold value in all theobtained similarities as singular features; and according to the singular feature set formed by the singular features and a preset model training algorithm, training the deep learning model again to complete online learning of the deep learning model, thereby improving the noise robustness of the deep learning model by introducing a suppression signal, and improving the model recognition precisionthrough personalized training.

Description

technical field [0001] The invention belongs to the technical field of deep learning, and in particular relates to an online learning method, device, equipment and medium of a deep learning model. Background technique [0002] Online learning (Online Learning) is not a model, but a model training method. Online learning can optimize and adjust the original prediction model in real time and quickly according to the online feedback data after the prediction model is trained and launched, so that The adjusted prediction model reflects online changes in a timely manner and improves the accuracy of online predictions. However, because the data used online is different from pure offline test data, it often contains certain noise. This dynamic learning characteristic and the complexity of the data The uniqueness makes online learning have higher requirements for the model in terms of scalability, anti-noise ability, and memory utility. [0003] At present, most online learning alg...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an online learning method, device, equipment and medium of a deep learning model, aiming to solve the problem that the existing technology cannot provide an effective The online learning method of the deep learning model leads to the problems of poor anti-noise ability of the deep learning model and low accuracy of model recognition

Images