Selected article for: "experimental method and model train"

Author: ji, d.; zhao, y.; zhang, z.; zhao, q.
Title: Research on Recognition Method of COVID-19 Images Based on Deep Learning
  • Cord-id: wsjv3x5k
  • Document date: 2020_12_11
  • ID: wsjv3x5k
    Snippet: In view of the large demand for new coronary pneumonia covid19 image recognition samples,the recognition accuracy is not ideal.In this paper,a new coronary pneumonia positive image recognition method proposed based on small sample recognition. First, the CT image pictures are preprocessed, and the pictures are converted into the picture formats which are required for transfer learning. Secondly, perform small-sample image enhancement and expansion on the converted picture, such as miscut transfo
    Document: In view of the large demand for new coronary pneumonia covid19 image recognition samples,the recognition accuracy is not ideal.In this paper,a new coronary pneumonia positive image recognition method proposed based on small sample recognition. First, the CT image pictures are preprocessed, and the pictures are converted into the picture formats which are required for transfer learning. Secondly, perform small-sample image enhancement and expansion on the converted picture, such as miscut transformation, random rotation and translation, etc.. Then, multiple migration models are used to extract features and then perform feature fusion. Finally,the model is adjusted by fine-tuning.Then train the model to obtain experimental results. The experimental results show that our method has excellent recognition performance in the recognition of new coronary pneumonia images,even with only a small number of CT image samples.

    Search related documents:
    Co phrase search for related documents
    • abnormality detection and accurate timely: 1
    • accuracy improve and activation function: 1