Method and device for identifying noise in image sample set, equipment and storage medium
An image sample set and image sample technology, applied in the field of machine learning, can solve problems such as unresponsiveness, time-consuming, high computing resource requirements, etc., to achieve the effect of improving cleanliness, reducing time-consuming, and increasing speed
Pending Publication Date: 2021-01-15
TENCENT TECH (SHENZHEN) CO LTD
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However, this solution requires repeated training of the network, which makes the sample screening process very time-consuming and requires high computing resources, which makes it impossible to quickly respond to some urgent needs. For example, it takes a lot of time to face a rapidly spreading infectious disease. It is not acceptable to perform training data filtering
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[0033] Artificial intelligence is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the nature of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines, so that the machines have the functions of perception, reasoning and decision-making. Artificial intelligence technology is a comprehensive subject that involves a wide range of fields, including both hardware-level technology and software-level technology. Artificial intelligence basic technologies generally include techno...
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The invention relates to the technical field of machine learning, in particular to a method and device for recognizing noise in an image sample set, equipment and a storage medium. The method comprises the following steps of training a model in a first fitting state based on the image sample set until the model enters a second fitting state, wherein the fitting state of the model represents the fitting degree of the model and the image sample set; wherein zero or at least one intermediate fitting state is included between the first fitting state and the second fitting state; wherein the fitting state of the model is determined based on a preset standard model; obtaining a loss value corresponding to each fitting state of each image sample in the image sample set; calculating a loss statistical value of each image sample according to the loss value corresponding to each fitting state of each image sample; and identifying a noise image sample in the image sample set according to the lossstatistical value corresponding to each image sample in the image sample set.
Description
technical field [0001] The present invention relates to the technical field of machine learning, in particular to a method, device, equipment and storage medium for identifying noise in an image sample set. Background technique [0002] With the research and progress of artificial intelligence (AI) technology, AI technology has been researched and applied in many fields, such as finance, medical treatment and game industry. [0003] In the field of intelligent medical care, machine learning technology can be used to process relevant medical images to realize the identification of disease attributes. Specifically, the machine learning model can be trained through several manually labeled training sample pictures, and the trained machine learning model can be used to determine disease areas and identify disease attributes in related medical image pictures. When training a machine learning model, it is necessary to collect multiple medical images of diseases as training sample...
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IPC IPC(8): G06T7/00G06T5/00
CPCG06T7/0012G06T2207/20081G06T2207/10081G06T2207/30201G06T2207/30016G06T5/70
Inventor 李悦翔陈嘉伟魏东马锴郑冶枫
Owner TENCENT TECH (SHENZHEN) CO LTD