Kernkonzepte
A novel drone detection algorithm with modified backbone and multiple pyramid feature maps enhancement structure (MDDPE) is proposed to improve the accuracy and robustness of drone detection.
Zusammenfassung
The paper presents a novel drone detection algorithm called MDDPE that utilizes a modified backbone and multiple pyramid feature maps enhancement strategies to improve the performance of drone detection.
Key highlights:
- The modified backbone combines the concepts of Resnet and U-Net to extract more discriminative and robust features for drone detection.
- The feature maps supplement function and feature maps recombination enhancement function are proposed to leverage different levels of information in the feature maps to produce more robust features.
- An improved anchor matching strategy, called Tailored Improved Anchor Matching (TIAM), is introduced to better align the anchors with the ground truth drone bounding boxes, leading to improved initialization for the regressor.
- Extensive experiments are conducted on popular drone detection benchmarks, demonstrating the superiority of the proposed MDDPE over state-of-the-art detectors.
- The robustness of MDDPE is evaluated across various drone detection scenarios, including different environments, scales, and drone types.
Statistiken
The statistics about yearly drone-related injuries published by US emergency departments.
Zitate
"Visual image-based drone detection has additional advantages as it can provide valuable information about the drone's location, trajectory, and identity."
"Although both one-stage and two-stage algorithm have been significant improvements in both the speed and accuracy of object detection algorithms, these improvements have mainly focused on enhancing medium and large-scale objects without significantly slowing down the speed."