Multi-scale pooling learning for camouflaged instance segmentation-Reference-Cited by-同舟云学术

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Multi-scale pooling learning for camouflaged instance segmentation

Published:2024-03 Issue:5 Volume:54 Page:4062-4076
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Li Chen^ORCID,Jiao Ge^ORCID,Yue Guowen,He Rong,Huang Jiayu

Funder

the Postgraduate Scientific Research Innovation Project of Hunan Province

Hunan Provincial Natural Science Foundation of China

The Science and Technology Plan Project of Hunan Province

The 14th Five-Year Plan Key Disciplines and Application-oriented Special Disciplines of Hunan Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10489-024-05369-2.pdf

Reference60 articles.

1. Fan D-P, Ji G-P, Cheng M-M, Shao L (2021) Concealed object detection. IEEE Trans Pattern Anal Mach Intell 44(10):6024–6042

2. Pang Y, Zhao X, Xiang T-Z, Zhang L, Lu H (2022) Zoom in and out: a mixed-scale triplet network for camouflaged object detection. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp 2160–2170

3. Long J, Shelhamer E, Darrell T (2015) Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp 3431–3440

4. He K, Gkioxari G, Dollár P, Girshick R (2017) Mask R-CNN. In: Proceedings of the IEEE international conference on computer vision. pp 2961–2969

5. Zhou Z, Siddiquee Md MR, Tajbakhsh N, Liang J (2018) Unet++: a nested U-Net architecture for medical image segmentation. In: Deep learning in medical image analysis and multimodal learning for clinical decision support: 4th international workshop, DLMIA 2018, and 8th international workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings 4. Springer, pp 3–11

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