Quantitative results of the cross-modal interaction fusion module. (The best results are shown in bold black).

Quantitative results of the cross-modal interaction fusion module. (The best results are shown in bold black).

<p>Quantitative results of the cross-modal interaction fusion module. (The best results are shown in bold black).</p>

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Bibliographic Details
Main Author:	Runqing Li (1827358) (author)
Other Authors:	Ling Yu (330944) (author), Zijian Jiang (3411935) (author), Fanglin Niu (6188366) (author)
Published:	2025
Subjects:	Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified spatial layout information salient object detection recent years due model &# 8217 dimensional dynamic convolution convolutional neural networks highlighting salient objects garnered significant attention extracting local details texture details small objects attention mechanism xlink "> rely solely relate high prediction mapping named cignet modal interactive mcfm ), level features geometric morphology excellent performance depth images depth features complex scenes cnns ), accurately recognising
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