Model construction method and device, terminal device and medium

A technology for building models and models, applied in biological neural network models, neural architectures, character and pattern recognition, etc. It can solve the problems of low recognition efficiency of face detection models, and achieve the effect of improving efficiency and reducing resource occupancy.

Pending Publication Date: 2020-02-14
SHENZHEN INTELLIFUSION TECHNOLOGIES CO LTD
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Problems solved by technology

[0004] In view of this, the embodiment of the present application provides a method, device, terminal device and computer-readable storage medium for constructing a model, so as to solve the problem of low recognition efficiency of a face detection model in the existing face image recognition process. The problem

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  • Model construction method and device, terminal device and medium
  • Model construction method and device, terminal device and medium
  • Model construction method and device, terminal device and medium

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Embodiment Construction

[0039] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0040] see figure 1 , figure 1 It is an implementation flowchart of a method for building a model provided in the embodiment of this application. In this embodiment, the method for constructing a model is used to identify the gland cavity and the margin of the gland on the gland image, and its execution body is a computer terminal device, for example, a computer or server for model construction or model optimization.

[0041] It should be noted that in all the embodiments of this application, the construction of the model is based on the existing model, and the existing ...

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Abstract

The method is suitable for the technical field of model construction, and provides a model construction method, a model construction device, a terminal device and a medium. The model construction method comprises the following steps: determining a convolution layer queue from a trained face detection model; then, based on the channel weight of each feature channel of each convolution layer in theconvolution layer queue and a preset channel deletion proportion, deleting the feature channels in the convolution layer queue; arranging the convolution layers according to the arrangement sequence of the convolution layers in the convolution layer queue; performing channel deletion on each convolution layer in sequence. According to the method, the convolution layer is not deleted in the new face detection model, and only part of channels in the convolution layer are deleted, so that the resource occupancy rate when the new face detection model is operated can be reduced under the conditionof ensuring that the face detection accuracy is not changed, and meanwhile, the face image recognition efficiency is improved.

Description

technical field [0001] The present application belongs to the technical field of model building, and in particular relates to a method, device, terminal equipment and computer-readable storage medium for building a model. Background technique [0002] Face detection technology is a biometric technology for identification based on human facial feature information. At the same time, face detection technology is also one of the most widely used technologies among various biometric technologies. For example, the unlocking of terminals, payment verification in consumer activities, or access control attendance, etc., are all applied to face detection technology. [0003] When recognizing face images, most of them use face image recognition models including neural networks to recognize the collected face images. Although the existing face image recognition models are equipped with a relatively complex feature extraction network layer, which can be used to extract various features...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V40/161G06N3/045G06F18/214
Inventor 黄德威冯展鹏胡文泽
Owner SHENZHEN INTELLIFUSION TECHNOLOGIES CO LTD
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