Small target detection algorithm based on multi-branch stacking and new sampling transition module.

ABSTRACT: Aiming at the problem that the SSD algorithm does not fully extract the feature information contained in each feature layer, as well as the feature information is easily lost during the sampling process, which makes the feature expression ineffective and leads to insufficient performance in small target detection. In this paper, AMT-SSD is proposed, a small target detection algorithm that incorporates the multi-branch stacking and new sampling transition module of the attention mechanism. In this algorithm, the composite attention mechanism is utilized to improve the correlation of features of the samples to be detected in terms of spatial and channels, and the efficiency of the algorithm; secondly, multi-branch stacking module is used to extract multi-size features for each feature layer,

SUBMITTER: Lin Q 

PROVIDER: S-EPMC11259291 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature