An improved YOLOv8 lightweight detail dynamic fusion algorithm (LDDF-YOLO) is proposed, to remedy the insufficient adaptation capability of vanilla lightweight YOLOv8 in remote sensing object detection tasks and possesses robust detection performance in challenging remote sensing scenarios with dense small targets and complex backgrounds.
MELRNet is proposed, a Mamba-enhanced lightweight framework for remote sensing rotated object detection, where Mamba-style state space modeling is introduced into key semantic stages to capture long-range dependencies with linear complexity.
Ji-Yang Dong, Peipei Song, Yongchao Song et al.· IEEE Journal of Selected Top...· 0 citations
MFRA-YOLOv11, an enhanced YOLOv11s-based network for remote sensing small object detection under the horizontal bounding box paradigm, which integrates multiscale feature extraction and object region awareness to improve detection accuracy.
Wei Huang, Qiang Zhou, Lu Gao et al.· Remote Sensing· 0 citations
Small-objectdetection in remote sensing images remains challenging due to insufficient feature representation, weak texture information, complex backgrounds, and high sensitivity to localization errors. To address these issues, this article proposes a frequency–spatial collaborative enhancement detector, multilevel wav...
The future of the field lies in the transition from single-modality visual perception to multi-dimensional collaborative detection systems, and this review serves as a comprehensive reference for optimizing object detection algorithms tailored for complex remote sensing and low-altitude security environments.
Ke Gu· Computer Vision, Graphics an...· 0 citations
To address the issues of large scale variation, weak features of small objects, and complex background interference in optical remote sensing images, this paper proposes an attention-guided adaptive multi-scale fusion object detection method. In the feature extraction network, a Multi-scale Feature Extracted Module (MF...
The experimental results show that the mAP50 and mAP50-95 values of the improved algorithm on the DOTA subset are increased, and the lightweight degree of the algorithm is improved slightly, which proves the effectiveness of the improved algorithm.
Lin-Lin He, Rong-Chen Ma· International Conference on...· 0 citations
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