Recognition Method of Fish Image with Dynamic Deformation Based on Depth Learning Network Model
Journal of Coastal Research, ISSN: 1551-5036, Vol: 83, Issue: sp1, Page: 397-401
2018
- 2Citations
- 8Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
Due to the failure distortion correction of the fish image with dynamic deformation, there cognition accuracy of traditional fish image with dynamic deformation is not high, therefore, a recognition method of fish image with dynamic deformation based on deep learning network model is proposed in this paper. By dividing the fish image with dynamic deformation, the segmented image is made rotation synthesis, to realize the deformation correction. Based on the deep learning network model algorithm, the partial derivative value of each parameter of fish image with dynamic deformation is calculated, to determine the characteristics distribution point of the fish image with dynamic deformation, and realize the fish image recognition. The experimental results show that the proposed method can accurately recognize the fish image with dynamic deformation, and the recognition results are better.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85056115831&origin=inward; http://dx.doi.org/10.2112/si83-066.1; https://bioone.org/journals/journal-of-coastal-research/volume-83/issue-sp1/SI83-066.1/Recognition-Method-of-Fish-Image-with-Dynamic-Deformation-Based-on/10.2112/SI83-066.1.full; https://dx.doi.org/10.2112/si83-066.1; https://bioone.org/access-suspended
Coastal Education and Research Foundation
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