Experimental results of different λ with <i>L</i><sub><i>s</i></sub> loss function on the CDD datasets.

Experimental results of different λ with <i>L</i><sub><i>s</i></sub> loss function on the CDD datasets.

<p>In our proposed SAASNets detection framework, λ = 0.2.</p>

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Bibliographic Details
Main Author:	Shuai Pang (4447831) (author)
Other Authors:	Chaochao You (20642598) (author), Min Zhang (111999) (author), Baojie Zhang (511505) (author), Liyou Wang (20642601) (author), Xiaolong Shi (412458) (author), Yu Sun (18463) (author)
Published:	2025
Subjects:	Neuroscience Science Policy Space Science Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> interfered shared attention aggregation receptive field limits highly efficient channel head attention module cdd datasets show sharing channel information encode position details detecting different scales building change detection feature aggregation module scale local features irregular object buildings redundant information different stages detection performance feature extractor siamese network siamese features residual strategy position multi global features external factors experimental results encoding stage detailed semantics better accuracy
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Summary:	<p>In our proposed SAASNets detection framework, λ = 0.2.</p>

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