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Optimization and performance evaluation of ship image recognition algorithm at night and in a fog

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DOI: 10.23977/acss.2024.080405 | Downloads: 8 | Views: 37

Author(s)

Junzhe Ma 1, Jianhui Cui 1, Chaoqun Yang 1, Chongtian Gao 1, Jiashuo Chen 1, Junjie Zhang 1

Affiliation(s)

1 Maritime College, Tianjin University of Technology, Tianjin, 300384, China

Corresponding Author

Junzhe Ma

ABSTRACT

Environmental factors such as low light and fog significantly affect the performance of image recognition systems in ship night and foggy navigation. This paper studies the challenges of image recognition technology under these conditions, and proposes a series of optimization strategies, including image enhancement technology and multimodal data fusion, to improve the accuracy and stability of image recognition. We've also made improvements to address the limitations of traditional image recognition technologies, including improved resolution and contrast, enhanced noise suppression, and real-time data processing capabilities for optimized algorithms. In addition, this paper evaluates the performance of the algorithm in terms of accuracy, response time, robustness and user convenience through quantitative evaluation criteria. The optimization method of this study not only improves the effect of image recognition, but also provides valuable technical guidance for the design and implementation of ship navigation system at night and foggy weather.

KEYWORDS

Ship night, image recognition, algorithm optimization, performance evaluation

CITE THIS PAPER

Junzhe Ma, Jianhui Cui, Chaoqun Yang, Chongtian Gao, Jiashuo Chen, Junjie Zhang, Optimization and performance evaluation of ship image recognition algorithm at night and in a fog. Advances in Computer, Signals and Systems (2024) Vol. 8: 32-38. DOI: http://dx.doi.org/10.23977/acss.2024.080405.

REFERENCES

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