Image identification method based on depth learning and transfer learning

A technology of transfer learning and image recognition, applied in the field of image recognition, can solve problems such as long training time, difficulty in obtaining training picture data, poor model performance, etc., and achieve the effect of shortening training time and good performance

Inactive Publication Date: 2017-07-28
NANJING ILUVATAR COREX TECH CO LTD (DBA ILUVATAR COREX INC NANJING)
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AI Technical Summary

Problems solved by technology

However, we see that machine learning algorithms have a key problem in current image recognition research: a large amount of labeled training image data in some emerging fields is very difficult to obtain
For image recognition in the medical field, due to the lack o

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  • Image identification method based on depth learning and transfer learning
  • Image identification method based on depth learning and transfer learning
  • Image identification method based on depth learning and transfer learning

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Embodiment Construction

[0019] In order to make the object, technical solution and advantages of the present invention clearer, the present invention 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 invention, not to limit the present invention.

[0020] Unless the context clearly states otherwise, the number of elements and components in the present invention can exist in a single form or in multiple forms, and the present invention is not limited thereto. Although the steps in the present invention are arranged with labels, they are not used to limit the order of the steps. Unless the order of the steps is clearly stated or the execution of a certain step requires other steps as a basis, the relative order of the steps can be adjusted. It can be understood that the term "and / or" used herein refers to and covers any and all possible combina...

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Abstract

The invention provides an image identification method based on depth learning and transfer learning. The image identification method based on depth learning and transfer learning includes the following steps: 1) a preparation step: reading a pre-training model, reading an image directory, and dividing a training set, a verification set and a test set; 2) a training step: constructing a full connection neural network classifier, taking the image set as input of the pre-training model, and using the output of the pre-training model to update the full connection neural network classifier; and 3) a storage step: storing the model result. The image identification method based on depth learning and transfer learning has the advantages of integrating with the application of depth learning and transfer learning so as to provide a relatively accurate bladder cancer diagnosis result for a user, on the basis of the extremely limited training time and training sample quantity.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to an image recognition method based on deep learning and transfer learning. Background technique [0002] With the advent of the era of big data, deep learning technology is increasingly used in the application of image recognition. Deep learning is a powerful technique derived from artificial neural networks. The artificial neural network is inspired by the neural network of natural creatures. By constructing multi-level neurons and repeated training with a large amount of data, it can achieve the ability to accurately recognize images similar to humans. [0003] In the field of image recognition, deep learning technology has been proved to be the most effective means by numerous facts. Theoretically, a model with more parameters has higher complexity and greater capability, but it also means that the training efficiency is relatively lower and it is easier...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2414
Inventor 吕艳洁戴川
Owner NANJING ILUVATAR COREX TECH CO LTD (DBA ILUVATAR COREX INC NANJING)
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