A picture garbage recognition method based on deep learning

A technology of deep learning and recognition methods, applied in the direction of character and pattern recognition, instruments, biological neural network models, etc., can solve the problems of difficult recognition methods, high distortion of picture content, etc., to avoid artificial design features, good feature properties, and economical Computational and training cost effects

Pending Publication Date: 2019-06-28
君库(上海)信息科技有限公司
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Problems solved by technology

[0004] In the actual production environment, a considerable number of pictures have a very large aspect ratio. Direct scal

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  • A picture garbage recognition method based on deep learning
  • A picture garbage recognition method based on deep learning
  • A picture garbage recognition method based on deep learning

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Embodiment Construction

[0035] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative work all belong to the protection scope of the present invention.

[0036] see Figure 1-4 , the present invention provides a kind of technical scheme: a kind of picture rubbish identification method based on deep learning, comprises the following steps:

[0037] S1: Establish a large-scale image training set, train a deep learning classifier based on convolutional neural network in the training set, and extract the convolutional layer as a deep feature extractor;

[0038] S2: Build a single nonlinear classifier, input ...

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Abstract

The invention discloses a picture garbage recognition method based on deep learning, and the method comprises the following steps: S1, building a large-scale picture training set, training a deep learning classifier based on a convolutional neural network in the training set, and extracting a convolutional layer in the deep learning classifier as a deep feature extractor; S2, constructing a singlenonlinear classifier, and inputting pictures in the high-quality picture library and the picture garbage library into the depth feature extractor obtained in the step S1 to obtain a feature representation vector; S3, taking the feature vector obtained in the step S2 as the input of a nonlinear classifier, and carrying out supervised learning by utilizing a corresponding tag to obtain an availablepicture garbage classifier; And S4, cutting the long image through a sliding window to obtain a plurality of pictures, extracting each segment of feature by using a depth feature extractor, classifying by using a picture garbage classifier, and comprehensively integrating each result to obtain a final result.

Description

technical field [0001] The invention relates to the technical field of computer picture processing, in particular to a method for identifying picture garbage based on deep learning. Background technique [0002] With the development of Internet technology, the amount of information stored on the network has increased tremendously, but its content composition is more complex, including a lot of low-quality and high-noise spam, and users have to spend a lot of time and energy to filter various information. class information. From the perspective of image search and classification, irrelevant or low-quality images will reduce user experience, such as food when searching for "landscape" and advertisements when searching for "architecture". If these can be automatically filtered out, it can Help users save a lot of time and effort. [0003] Existing image recognition methods are mainly aimed at the recognition of specific objects on regular data, which require a specific data s...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04
Inventor 洒海涛韩炜
Owner 君库(上海)信息科技有限公司
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