Research on Water Surface Environment Perception Method Based on Visual and Positional Information Fusion

Qin Na, Zhe Zuo, Ning Xu, Zhen Yu Zhang*, Yi Lu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The water surface environment characterised by complexity and variability, is heavily influenced by weather. To address this problem, this paper proposes a water surface environment perception network based on the fusion of visual and positional information, and proposes an encoder-decoder based semantic segmentation neural network for classifying the pixel points of the input image into three categories: water, sky and environment (obstacles).

Original languageEnglish
Title of host publicationAdvanced Computational Intelligence and Intelligent Informatics - 8th International Workshop, IWACIII 2023, Proceedings
EditorsBin Xin, Naoyuki Kubota, Kewei Chen, Fangyan Dong
PublisherSpringer Science and Business Media Deutschland GmbH
Pages50-62
Number of pages13
ISBN (Print)9789819975891
DOIs
Publication statusPublished - 2024
Event8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2023 - Beijing, China
Duration: 3 Nov 20235 Nov 2023

Publication series

NameCommunications in Computer and Information Science
Volume1931 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2023
Country/TerritoryChina
CityBeijing
Period3/11/235/11/23

Keywords

  • Attentional mechanisms
  • Positional information
  • Semantic segmentation

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