Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308457255> ?p ?o ?g. }
- W4308457255 abstract "As the development of deep learning and the continuous improvement of computing power, as well as the needs of social production, target detection has become a research hotspot in recent years. However, target detection algorithm has the problem that it is more sensitive to large targets and does not consider the feature-feature interrelationship, which leads to a high false detection or missed detection rate of small targets. An small target detection method (C-SSD) based on improved SSD is proposed, that replaces the backbone network VGG-16 of the SSD network with the improved dense convolution network (C-DenseNet) network to achieves further feature fusion through fast connections between dense blocks. The Introduction of residuals in the prediction layer and DIoU-NMS further improves the detection accuracy. Experimental results demonstrate that C-SSD outperforms other networks at three different image scales and achieves the best performance of 83. A 8% accuracy on the PASCAL VOC2007 test set, proving the effectiveness of the algorithm. C-SSD achieves a better balance of speed and accuracy, showing excellent performance in rapid detection of small targets." @default.
- W4308457255 created "2022-11-12" @default.
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- W4308457255 date "2022-11-06" @default.
- W4308457255 modified "2023-10-18" @default.
- W4308457255 title "Improved single shot detection using <scp>DenseNet</scp> for tiny target detection" @default.
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- W4308457255 doi "https://doi.org/10.1002/cpe.7491" @default.
- W4308457255 hasPublicationYear "2022" @default.
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