Frontiers of Data and Computing ›› 2020, Vol. 2 ›› Issue (6): 30-41.

doi: 10.11871/jfdc.issn.2096-742X.2020.06.004

• Key Technology & Application of Modern Service Industry • Previous Articles     Next Articles

Computer Vision Detection and Analysis of Mesoscale Eddies in Marine Science

SHEN Biao(),CHEN Yang,YANG Chen,LIU Bowen   

  1. Ocean University of China, Qingdao, Shandong 266100, China
  • Received:2020-08-08 Online:2020-12-20 Published:2020-12-29
  • Contact: SHEN Biao


[Objective] Mesoscale eddy is an important research topic in the field of marine science. With the support of deep neural network in the artificial intelligence field, computer vision is combined with ocean field technology to promote the application and development of intelligent recognition technology of mesoscale eddy. [Methods] Based on Mask-RCNN algorithm, a deep learning object detection algorithm is applied to the detection of mesoscale eddies. Combined with the multi-modal satellite remote sensing image data, the mesoscale eddies in the ocean can be identified, classified and segmented. [Results] The traditional method can only detect the location and size of mesoscale eddies. In this paper, multi-modal information is adopted to locate, classify and segment the mesoscale eddies. [Conclusions] Artificial intelligence has great application potential in recognizing and tracking mesoscale eddies. But the evaluation indexes of eddy detection still need to be further improved to promote the rapid and efficient development of deep learning detection of mesoscale eddies.

Key words: mesoscale eddy, object detection, deep learning, multimodal data fusion