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A drone detector with modified backbone and multiple pyramid featuremaps enhancement structure (MDDPE)

arXiv 2405.02882 ↗First posted 5 May 2024cs.CVcited by 0

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Abstract (arXiv)

This work presents a drone detector with modified backbone and multiple pyramid feature maps enhancement structure (MDDPE). Novel feature maps improve modules that uses different levels of information to produce more robust and discriminatory features is proposed. These module includes the feature maps supplement function and the feature maps recombination enhancement function.To effectively handle the drone characteristics, auxiliary supervisions that are implemented in the early stages by employing tailored anchors designed are utilized. To further improve the modeling of real drone detection scenarios and initialization of the regressor, an updated anchor matching technique is introduced to match anchors and ground truth drone as closely as feasible. To show the proposed MDDPE's superiority over the most advanced detectors, extensive experiments are carried out using well-known drone detection benchmarks.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 29 references that are in the map. First posted on arXiv 5 May 2024.

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15 of 29 references.

References · 15

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  3. 2017Mask R-CNNcited by 7,259
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  8. 2018YOLOv3: An Incremental Improvementcited by 2,652
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  11. 2017Understanding Convolution for Semantic Segmentationcited by 168
  12. 2018Pyramid Attention Network for Semantic Segmentationcited by 148
3 more
  1. 2017DSSD : Deconvolutional Single Shot Detectorcited by 130
  2. 2017FSSD: Feature Fusion Single Shot Multibox Detectorcited by 42
  3. 2017A Deep Learning Approach to Drone Monitoringcited by 16

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