Method and device for detecting spot defect of face skin based on deep learning

A facial skin and deep learning technology, applied in neural learning methods, computer components, image data processing, etc., can solve the problems of inability to provide scientific and rigorous references for skin defect assessment and treatment, and achieve less computing overhead, false positives and negative negatives Fewer, more accurate results

Inactive Publication Date: 2018-11-30
北京羽医甘蓝信息技术有限公司
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Problems solved by technology

[0004] In view of this, the present invention provides a method and device for detecting facial skin point defects based on deep learning, which can

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  • Method and device for detecting spot defect of face skin based on deep learning
  • Method and device for detecting spot defect of face skin based on deep learning
  • Method and device for detecting spot defect of face skin based on deep learning

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[0021] The following describes exemplary embodiments of the present invention with reference to the accompanying drawings, which include various details of the embodiments of the present invention to facilitate understanding, and should be regarded as merely exemplary. Therefore, those of ordinary skill in the art should realize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Likewise, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0022] To enable those skilled in the art to better understand, the following describes in detail the relevant knowledge of different types of facial skin punctate defects.

[0023] (1) Pigmented nevus

[0024] Pigmented nevus, also referred to as nevus stain, or mole, is the most common benign tumor of the skin composed of mole cells that normally contain pigment, and oc...

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Abstract

The invention provides a method and a device for detecting a spot defect of a face skin based on deep learning. The method comprises the steps of acquiring a training data set; constructing a convolutional neural network, and training the convolutional neural network by use of the training data set to obtain a detection model, wherein the convolutional neural network has the following characteristics: multi-layer convolutional characteristic extraction is performed on a sample to obtain different hierarchies of characteristic graphs, then, sampling is performed by use of sampling frames with multiple sizes and shapes to obtain sampling result corresponding to different hierarchies, then all of the sampling results are classified by use of a softmax loss function and a position is predictedby use of an L1 loss function, a loss value obtained by calculation is returned to a front end of the convolutional neural network, and a convolutional neural network parameter is adjusted b y use ofa gradient descent method; and segmenting a to-be-detected image into test image blocks, inputting all test image blocks into the detection model in a traversal manner to obtain corresponding image block detection results, and then splicing all of the image block test results into a complete image detection result.

Description

technical field [0001] The invention relates to the technical field of computers and software, in particular to a method and device for detecting facial skin point defects based on deep learning. Background technique [0002] With the improvement of living standards, the public began to pursue the beauty and health of facial skin. Common facial skin defects can be roughly divided into facial skin point defects and facial skin point defects according to shape, area and distribution. Among them, facial skin point defects include pigment nevus, acne, acne marks, etc., which are characterized by small area, similar point shape, and usually independent distribution. [0003] Automated detection of such point-like skin defects is generally used for batch processing or quantitative statistical analysis of skin defects. Most of the existing automatic detection algorithms for point-like skin defects are based on traditional computer vision technology, that is, according to the colo...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06T2207/20081G06T2207/20084G06T2207/30204G06T2207/30201G06T2207/30088G06N3/08G06N3/045G06F18/24G06F18/214
Inventor 白海龙徐通汪子晨
Owner 北京羽医甘蓝信息技术有限公司
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