pone.0296314.g006.tif (914.02 kB)
Deformable convolution introduced into SSD networks.
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posted on 2024-01-05, 18:31 authored by Zhi-Ben Yin, Fu-Yong Liu, Hui Geng, Ya-Jun Xi, De-Bin Zeng, Chun-Jing Si, Ming-Deng ShiDeformable convolutional sampling points adaptive offset. (a) Standard convolution sampling point; (b) Deformable convolutional sampling point adaptive offset.
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traditional convolution layertarget detail featuressingle shot multimultiple location detailsjujubessd reached 97href =" mailtoexperimental results demonstratedeformable convolutional networksbalanced feature pyramid61 %, respectively1 %, representingparameter information obtainedmethod called jujubessdidentifying disease spotsdisease spot regionsmean average precisiondiv >< pdisease spotsweak informationspot detectionproposed methodvarying sizesvarying densitiesvaried sizesprecise detectionpractical applicationpaper proposesoriginal algorithmobjectives duefaster rexisting algorithmsdcns ).data augmentationcurrent algorithmsbox detectorartificial collectionapproximately 6
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