Upernet optimisation and application to mousehole segmentation

Kai Li; Bingming Tang; Haiyang Li; Yunpeng Jin; Jieteng Jiang; Li Chunmei

doi:10.1117/12.2667353

1 March 2023 Upernet optimisation and application to mousehole segmentation

Kai Li, Bingming Tang, Haiyang Li, Yunpeng Jin, Jieteng Jiang, Li Chunmei

Proceedings Volume 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022); 125880M (2023) https://doi.org/10.1117/12.2667353
Event: International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 2022, Chongqing, China

Abstract

The evaluation of grassland degradation is an important part of ecological conservation research, and rodent infestation is a significant factor in grassland degradation. The presence of a large number of mouseholes means that the environmental balance of grassland has been destroyed, so the coverage of mouseholes can be used as an evaluation method for grassland degradation levels. In this paper, the image segmentation method is used to segment the mousehole images, Upernet is used as the segmentation network, and Swin Transformer as the Backbone. FAM and FSM modules are added to the Upernet network to solve the target misalignment problem when upsampling the network. The mIoU is improved by 5.3% according to the experimental results.

Citation Download Citation

Kai Li, Bingming Tang, Haiyang Li, Yunpeng Jin, Jieteng Jiang, and Li Chunmei "Upernet optimisation and application to mousehole segmentation", Proc. SPIE 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 125880M (1 March 2023); https://doi.org/10.1117/12.2667353

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KEYWORDS

Image segmentation

Data modeling

Transformers

Semantics

Education and training

Statistical modeling

Ecosystems

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