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Multiplexing Multi-Scale Features Network for Salient Target Detection.
- Source :
- Applied Sciences (2076-3417); Sep2024, Vol. 14 Issue 17, p7940, 12p
- Publication Year :
- 2024
-
Abstract
- This paper proposes a multiplexing multi-scale features network (MMF-Network) for salient target detection to tackle the issue of incomplete detection structures when identifying salient targets across different scales. The network, based on encoder–decoder architecture, integrates a multi-scale aggregation module and a multi-scale visual interaction module. Initially, a multi-scale aggregation module is constructed, which, despite potentially introducing a small amount of noise, significantly enhances the high-level semantic and geometric information of features. Subsequently, SimAM is employed to emphasize feature information, thereby highlighting the significant target. A multi-scale visual interaction module is designed to enable compatibility between low-resolution and high-resolution feature maps, with dilated convolutions utilized to expand the receptive field of high-resolution feature maps. Finally, the proposed MMF-Network is tested on three datasets: DUTS-Te, HUK-IS, and PSCAL-S, achieving scores of 0.887, 0.811, and 0.031 in terms of its F-value SSIM and MA, respectively. The experimental results demonstrate that the MMF-Network exhibits a superior performance in salient target detection. [ABSTRACT FROM AUTHOR]
- Subjects :
- OSCILLATOR strengths
MULTIPLEXING
NOISE
Subjects
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 14
- Issue :
- 17
- Database :
- Complementary Index
- Journal :
- Applied Sciences (2076-3417)
- Publication Type :
- Academic Journal
- Accession number :
- 179650463
- Full Text :
- https://doi.org/10.3390/app14177940