Image processing model training method and system, computer equipment and storage medium
A model training and image processing technology, which is applied to computer components, computing, computing models, etc., can solve problems such as inconsistency in client data distribution and low performance of federated learning models, and achieve the goal of improving training efficiency and accuracy, and shortening distances Effect
Active Publication Date: 2022-07-22
PING AN TECH (SHENZHEN) CO LTD
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[0004] The embodiment of the present invention provides an image processing model training method, system, computer equipment and storage medium to solve the problem of low performance of the federated learning model due to inconsistent distribution of different client data
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[0026] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
[0027] The image processing model training method provided by the embodiment of the present invention, the image processing model training method can be applied such as figure 1 in the application environment shown. Specifically, the image processing model training method is applied in an image processing model training system, and the image processing model training system includes: figure 1 The shown client and server, the system client a...
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The invention relates to the technical field of artificial intelligence, and discloses an image processing model training method and system, computer equipment and a storage medium, and the method comprises the steps: constructing an initial local model based on service model parameters; performing feature extraction on the sample image by adopting a twin network model to obtain a first loss value; a twin network model is constructed based on an initial local model; acquiring global image features, and performing feature extraction on the sample image through the initial local model to obtain local image features; determining a second loss value according to the global image feature and the local image feature; updating the initial local model according to the first loss value and the second loss value to obtain an updated local model; updating the local model to associate with the updated model parameters; and sending the updated model parameters to a server, so that the server updates the service global model according to the updated model parameters to obtain an image processing model. According to the invention, the training efficiency and accuracy of the image processing model are improved.
Description
technical field [0001] The present invention relates to the technical field of detection models, in particular to an image processing model training method, system, computer equipment and storage medium. Background technique [0002] With the advent of the era of big data, data processing technology is developing more and more rapidly, such as recommendation systems, voice assistants, etc. are widely used, but as time goes by, applications often need to be adjusted according to the feedback data from different clients Update the application to meet the needs of different customers. [0003] In the prior art, a unified federated learning model is generally obtained by training according to model parameters of different clients by means of federated learning. However, the method of federated learning has the following shortcomings: due to the inconsistent distribution of data on different clients, the performance of the federated learning model may be low; and in order to pro...
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Login to View More IPC IPC(8): G06V10/764G06V10/42G06K9/62G06N20/00
CPCG06N20/00G06F18/2413
Inventor 司世景王健宗张传尧
Owner PING AN TECH (SHENZHEN) CO LTD