Neural network training and image recognition method and device, equipment and storage medium

A neural network and training method technology, applied in the computer field, can solve problems such as the complexity of pedestrian re-identification tasks, achieve the effects of reducing inaccurate segmentation prediction results, improving accuracy, and improving accuracy

Pending Publication Date: 2020-04-17
BEIJING SENSETIME TECH DEV CO LTD
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Problems solved by technology

[0003] However, as the task of pedestrian re-identification becomes more and more complex, the requirements for the recognition accur...

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  • Neural network training and image recognition method and device, equipment and storage medium
  • Neural network training and image recognition method and device, equipment and storage medium
  • Neural network training and image recognition method and device, equipment and storage medium

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Embodiment Construction

[0139] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numbers in the figures indicate functionally identical or similar elements. While various aspects of the embodiments are shown in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0140] The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or better than other embodiments.

[0141] The term "and / or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations. In addition, the term "at least one" herein ...

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Abstract

The invention relates to a neural network training and image recognition method and device, equipment and a storage medium. The training method comprises the following steps: extracting a neural network model from training data through initial features to obtain an initial feature map of a target object; processing the initial feature map through a first initial recognition neural network model toobtain a first prediction result; processing the initial feature map through a second initial recognition neural network model to obtain a second prediction result; procssing the initial feature mapthrough an initial segmentation neural network model to obtain a segmentation result; and updating the initial feature extraction neural network model according to the first prediction result, the second prediction result and the segmentation result to obtain a trained feature extraction neural network model. Through the process, the network capacity, the generalization ability and the extractionprecision of the feature extraction network model can be increased; meanwhile, the segmentation result obtained by using the model can enable the feature extraction network model obtained by trainingto have higher convergence degree and accuracy.

Description

technical field [0001] The present disclosure relates to the field of computer technology, in particular to a neural network training and image recognition method, device, device and storage medium. Background technique [0002] Pedestrian re-identification refers to a query picture of a pedestrian, and it is necessary to find all pictures of the same person in a large-scale data set. With the development of deep learning technology, pedestrian re-identification can be realized by neural network. [0003] However, as the task of pedestrian re-identification becomes more and more complex, the requirements for the recognition accuracy of the neural network are higher, and how to improve the recognition ability of the neural network has become an urgent problem to be solved. Contents of the invention [0004] The present disclosure proposes a training scheme for a neural network. [0005] According to an aspect of the present disclosure, a method for training a neural netwo...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/213G06F18/214G06F18/241
Inventor 兰宇时张学森
Owner BEIJING SENSETIME TECH DEV CO LTD
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