5 / 2018-03-28 22:10:43
A JOINT APPLICATION OF FUZZY LOGIC APPROXIMATION AND A DEEP LEARNING NEURAL NETWORK TO BUILD FISH CONCENTRATION MAPS BASED ON SONAR DATA
Fuzzy Logic,Neural network
全文待审
Juho Mäkiö / University of Applied Sciences Emden Leer
Dmitry Glukhov / Polotsk State University
Rykhard Bohush / Polotsk State University
Tatsiana Hlukhava / Polotsk State University
Iryna Zakharava / Polotsk State University
In this paper we propose a novel method for obtaining topographic maps of lakes, maps of fish concentration and a map of predator location based on the results of intelligent sonar data processing. The method uses an effective algorithm for the detection of fishes and other objects on sonar images based on the following steps: input frame separating into overlapping blocks, blocks-processing using convolutional neural networks (CNN) YOLO v2, and merging extracted bounding boxes around one object. To construct maps of the distribution of features along the lake, we propose a new method for constructing the approximation of GPS-referenced CNN results based on the original implementation of fuzzy logic.
重要日期
  • 06月15日

    2018

    会议日期

  • 04月01日 2018

    摘要截稿日期

  • 04月30日 2018

    初稿截稿日期

  • 05月10日 2018

    初稿录用通知日期

  • 05月20日 2018

    终稿截稿日期

  • 06月15日 2018

    注册截止日期

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