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Zhuang nationality minority costume segmentation method based on deep learning

A minority, deep learning technology, applied in the field of deep learning and image semantic segmentation, can solve the problems of low machine recognition efficiency, improve machine recognition efficiency, reduce over-fitting situations, and solve the effect of low machine recognition efficiency

Pending Publication Date: 2021-04-16
GUILIN UNIV OF ELECTRONIC TECH
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a deep learning-based segmentation method for clothing of Zhuang ethnic minorities, aiming to solve the technical problem of low machine recognition efficiency of Zhuang ethnic clothing in the prior art

Method used

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  • Zhuang nationality minority costume segmentation method based on deep learning
  • Zhuang nationality minority costume segmentation method based on deep learning
  • Zhuang nationality minority costume segmentation method based on deep learning

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Embodiment Construction

[0023] 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 designate 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 and are intended to explain the present invention and should not be construed as limiting the present invention.

[0024] In describing the present invention, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", The orientation or positional relationship indicated by "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than Nothing indicating or implying that a referenced device or element...

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Abstract

The invention discloses a Zhuang nationality minority costume segmentation method based on deep learning, and the method comprises the steps: building a minority costume image library, building a semantic segmentation model training model, and carrying out the Mosaic data enhancement preprocessing of an image to be recognized, so a smaller object can be recognized and the background of a detection object is enriched. Through image label smoothing operation, the situation of over-fitting is reduced, the risk that the model is too believed to predict the category is reduced, meanwhile, an assistant branch structure is used, a more reasonable semantic segmentation model training model is obtained, and the machine recognition efficiency is improved. The technical problem that in the prior art, the identification efficiency of a Zhuang nationality minority costume using machine is not high is solved.

Description

technical field [0001] The invention relates to the field of image semantic segmentation and the field of deep learning technology, in particular to a deep learning-based clothing segmentation method for Zhuang ethnic minorities. Background technique [0002] Ethnic costumes usually include ornaments, sleeves, tops, skirts, leggings, trousers and belts, etc., and there are many kinds. [0003] People distinguish clothing mainly through human observation, and usually identify the accessories, sleeves, tops, skirts, leggings, trousers and belts of ethnic minorities separately, so it is very dependent on the experience and experience of the recognizer. [0004] However, relying solely on manual recognition of large quantities of clothing can easily cause fatigue to the recognizer, and the recognition efficiency is low. Relying on manual supervision and decision-making often has problems such as low recognition efficiency. Contents of the invention [0005] The purpose of the...

Claims

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Application Information

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IPC IPC(8): G06T7/194G06T7/12G06T5/00G06T3/40G06K9/34G06K9/46G06K9/62G06N3/04G06N3/08
Inventor 覃琴颜靖柯王鑫李黄河王逸轩
Owner GUILIN UNIV OF ELECTRONIC TECH
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