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Image description method based on intra-layer and inter-layer joint global representation

An image description and global technology, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as bias, no explicit modeling of global features, missing objects, and relationships

Pending Publication Date: 2021-05-18
XIAMEN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide a more comprehensive and instructive global feature by modeling a more comprehensive and instructive global feature that connects different local Image description method based on joint global representation of intra-layer and inter-layer to improve the accuracy of generated description

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  • Image description method based on intra-layer and inter-layer joint global representation
  • Image description method based on intra-layer and inter-layer joint global representation

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Embodiment Construction

[0058] The following embodiments will describe the technical solutions and beneficial effects of the present invention in detail in conjunction with the accompanying drawings.

[0059] The purpose of the present invention is to solve the problem that the traditional transformer-based image description method does not explicitly model global features, resulting in missing objects and biased relationships. It proposes to connect different local features by modeling a more comprehensive and instructive global feature. information, thereby improving the accuracy of generated descriptions, and providing an image description method based on a joint global representation between layers within layers. The specific method flow is as figure 1 shown.

[0060] Embodiments of the present invention include the following steps:

[0061] 1) For the images in the image library, first use the convolutional neural network to extract the corresponding image features;

[0062] 2) Sen...

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Abstract

The invention discloses an image description method based on intra-layer and inter-layer joint global representation, and relates to artificial intelligence. The method comprises: the step 1, extracting a plurality of candidate areas of a to-be-described image and features corresponding to the candidate areas by adopting a target detector; and the step 2, inputting the features extracted in the step 1 into the trained neural network so as to output a description result of the to-be-described image. By utilizing the characteristics of a Transformer structure and explicitly modeling intra-layer and inter-layer joint global features, the global features of pictures are effectively utilized, object missing and relation bias existing between image description tasks are reduced, and the accuracy and comprehensiveness of generated sentences are improved; the method has very strong mobility and can be suitable for any image description model based on a Transformer structure, and the model performance is improved; and the problems of target missing and relation offset of image description are solved, complex multi-modal reasoning is expanded, description is automatically generated, and the method can be applied to the fields of image retrieval, blind navigation, automatic generation of medical reports and early education.

Description

technical field [0001] The invention relates to automatic image description in the field of artificial intelligence, in particular to an image description method based on intra-layer and inter-layer joint global representation for describing the objective content of the image in natural language based on the image. Background technique [0002] Automatic image description (Image Captioning) is an ultimate machine intelligence task proposed by the artificial intelligence community in recent years. Its task is to describe the objective content of the image in natural language for a given image. With the development of computer vision technology, tasks such as target detection, recognition, and segmentation can no longer meet people's production needs, and there is an urgent need for how to automatically and objectively describe image content automatically. Different from tasks such as target detection and semantic segmentation, automatic image description requires an overall a...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/049G06N3/082G06V10/40G06V10/44G06V2201/07G06N3/047G06N3/045G06F18/22
Inventor 孙晓帅纪荣嵘纪家沂
Owner XIAMEN UNIV
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