A method for improving field transformation phenomenon of image recognition models
An image recognition and model technology, applied in the field of computer vision, can solve the problems affecting the effect of genetic algorithm, insufficient image feature extraction, simple individual, etc., and achieve the effect of fully extracting image features, improving the phenomenon of domain transformation, and improving complex processes.
Active Publication Date: 2020-12-29
BEIJING UNIVERSITY OF CIVIL ENGINEERING AND ARCHITECTURE
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Problems solved by technology
[0005] 1. A simple random search method is used in the process of constructing attribute combinations, which cannot ensure a balanced search for all attributes, which affects the distribution of individuals in the genetic algorithm population
[0006] 2. Only 3 attributes are used as an attribute combination, resulting in too simple individuals in the population, which affects the effect of the entire genetic algorithm
[0008] 4. The convolutional neural network model constructed in the whole process is not perfect, which will lead to insufficient feature extraction of the image
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[0059] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.
[0060] Those skilled in the art will understand that unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the word "comprising" used in the description of the present invention refers to the presence of said features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, elements, components, and / or groups thereof. It will be understoo...
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According to the method for improving the field transformation phenomenon of the image recognition model, a genetic algorithm is applied, a weight value is given to each attribute, and the weight values of the attributes are continuously updated in the searching process of the attributes. The searched probability of each attribute is calculated according to the weight value of the attribute, the smaller the weight value is, the higher the searched probability of the attribute is, and otherwise, the smaller the searched probability is. The attributes are searched according to the searched probability of each attribute, and the search direction can be controlled, so that the condition that certain attributes are searched for too many times or too few times is avoided. Through combined application of the Equal function and the Sum function, screening of attribute combinations is completed, and the complex process of calculation is improved. In the whole process, a convolutional neural network which is constructed based on a Leaky Relu activation function and is provided with three convolutional layers is used, the phenomenon that neurons smaller than 0 cannot update parameters in themodel training process is avoided, and the purpose of fully extracting image features is achieved.
Description
technical field [0001] The invention relates to the technical field of computer vision, in particular to a method for improving the domain transformation phenomenon of an image recognition model. Background technique [0002] Image recognition refers to the use of computers to process, analyze and understand images, and is an important field of artificial intelligence. The recognition of the image by the computer is mainly based on the main features of the image, for example, there is a "circle" in the number "6", and there are two "circles" in the number "8". However, images in different fields often have different main features, such as the size of the image, the number of channels, the background color and other features will be generated for the image recognition model. However, in the recognition process, the computer cannot make independent dialectical judgments on the image like the human eye, and cannot directly eliminate the influence of some unnecessary image feat...
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Login to View More IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/214G06F18/241
Inventor 谭志刘兴业
Owner BEIJING UNIVERSITY OF CIVIL ENGINEERING AND ARCHITECTURE