Micro-video classification method and system based on missing data completion

A technology of missing data and classification methods, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as reducing the accuracy of micro-video classification tasks, achieve strong semantic representation capabilities, and ensure accuracy

Active Publication Date: 2021-11-16
SHANDONG JIANZHU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This will obviously reduce the accuracy of micro-video classification tasks in real scenes

Method used

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  • Micro-video classification method and system based on missing data completion
  • Micro-video classification method and system based on missing data completion
  • Micro-video classification method and system based on missing data completion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] Such as figure 1 As shown, this embodiment provides a micro-video classification method based on missing data completion. This embodiment uses this method as an example to illustrate the application of the server. It can be understood that this method can also be applied to terminals, and can also be applied to It includes terminals, servers and systems, and is realized through the interaction between terminals and servers. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or it can provide cloud services, cloud database, cloud computing, cloud function, cloud storage, network server, cloud communication, intermediate Cloud servers for basic cloud computing services such as software services, domain name services, security service CDN, and big data and artificial intelligence platforms. The terminal may be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart spe...

Embodiment approach

[0064] As one or more implementations, the two-way cyclic generative adversarial network includes: three cyclic generative adversarial networks, each cyclic generative adversarial network includes two directions, generating the second modality from the first modality and generating the second modality from the second modality Modality generates a first modal, where the first modal is a visual or audible modal or a text modal, the second modal is a visual or audible modal or a textual modal, and the first and The second modality is not the same.

[0065] Specifically, such as image 3 Shown: The features of the three modalities of the micro-video pass through three sets of cyclic generative adversarial networks to generate feature representations of other modalities respectively. Each set of recurrent generative adversarial networks includes two directions, generating modal B from modal A and generating modal A from modal B (generating modal C from modal B and generating modal...

Embodiment 2

[0092] This embodiment provides a micro-video classification system based on missing data completion.

[0093] A micro-video classification system based on missing data completion, including:

[0094] The classification module is configured to: based on the micro-videos with partial modal data missing, adopt the trained micro-video classification network to obtain the classification result of the micro-videos with partial modal data missing;

[0095] Model building module, it is configured as: described micro-video classification network comprises: Based on the micro-video that there is partial modal data missing, adopts two-way circulation to generate confrontation network, obtains the missing modality that complements micro-video; The original micro-video The missing modals of the modal and complementary micro-videos pass through the common subspace learning module to extract the semantic feature representation vector of the visual modality, the semantic feature representati...

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Abstract

The invention belongs to the technical field of micro-video classification, and provides a micro-video classification method and system based on missing data completion. The method comprises the following steps: based on a micro-video with partial modal data missing, adopting a trained micro-video classification network to obtain a classification result of the micro-video with partial modal data missing, wherein the micro-video classification network comprises the following steps: based on a micro-video with partial modal data missing, adopting a bidirectional cyclic generative adversarial network to obtain a missing modal of the complemented micro-video; extracting a visual mode semantic feature representation vector, a sound mode semantic feature representation vector and a text mode semantic feature representation vector from the original mode of the micro-video and the missing mode of the complemented micro-video through a common subspace learning module; and enabling the obtained visual modal semantic feature representation vector, the sound modal semantic feature representation vector and the text modal semantic feature representation vector to pass through a full connection layer to obtain a classification result of the micro-video with partial modal data missing.

Description

technical field [0001] The invention belongs to the technical field of micro-video classification, and in particular relates to a micro-video classification method and system based on missing data completion. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With the birth of the concept of Web 2.0 and the rapid development of the mobile Internet, social media platforms continue to emerge and gradually expand from the original PC terminal to the mobile terminal. At the same time, the media form of micro-video came into being. At present, there are many micro-video social media platforms on the market, such as Douyin, Xigua Video, Volcano Video, Kuaishou, etc. Micro-video classification plays an important role in the group display of videos and personalized recommendations for users, and is an important function of the micro-video platform....

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06N3/044G06F18/24G06F18/214
Inventor 郭杰马玉玲聂秀山刘萌袭肖明宁阳尹义龙
Owner SHANDONG JIANZHU UNIV
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