ArticleSensors (Basel, Switzerland)2020
UAV-YOLO: Small Object Detection on Unmanned Aerial Vehicle Perspective.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- LFC-YOLO: A Lightweight Feature-Complementary YOLO Framework for Small Object Detection in UAV-Based Visual Sensing.Sensors (Basel, Switzerland) · 2026Article
- Dynamic convolutional neural networks for altitude aware UAV object detection.Scientific reports · 2026Article
- Efficient real time small object detection framework in aerial images using edge awareness and dynamic convolution.Scientific reports · 2026Article
- Real-time object detection for unmanned aerial vehicles based on vision transformer and edge computing.Scientific reports · 2026Article
- AQF-Net: Adaptive query modeling and efficient feature fusion for UAV tiny-object detection.PloS one · 2026Article
- ESE-PWDNet: an efficient early-stage pine wilt disease detection network.Frontiers in plant science · 2026Article
- ClearSight-RS: A YOLOv5-Based Network with Dynamic Enhancement for Remote Sensing Small Target Detection.Sensors (Basel, Switzerland) · 2025Article
- GURLKNet gated unified reparameterized large kernel network for insulator defect detection.Scientific reports · 2025Article
- Dynamic small object feature enhancement and detection for remote sensing images.Scientific reports · 2025Article
- ASensors (Basel, Switzerland) · 2025Article
- MSConv-YOLO: An Improved Small Target Detection Algorithm Based on YOLOv8.Journal of imaging · 2025Article
- UAV-DETR: An Enhanced RT-DETR Architecture for Efficient Small Object Detection in UAV Imagery.Sensors (Basel, Switzerland) · 2025Article
- RSW-YOLO: A Vehicle Detection Model for Urban UAV Remote Sensing Images.Sensors (Basel, Switzerland) · 2025Article
- Rose-Mamba-YOLO: an enhanced framework for efficient and accurate greenhouse rose monitoring.Frontiers in plant science · 2025Article
- Bridging technology and ecology: enhancing applicability of deep learning and UAV-based flower recognition.Frontiers in plant science · 2025Article
- SOD-YOLOv8-Enhancing YOLOv8 for Small Object Detection in Aerial Imagery and Traffic Scenes.Sensors (Basel, Switzerland) · 2024Article
- Classification of Unmanned Aerial Vehicles Based on Acoustic Signals Obtained in External Environmental Conditions.Sensors (Basel, Switzerland) · 2024Article
- Accurate UAV Small Object Detection Based on HRFPN and EfficentVMamba.Sensors (Basel, Switzerland) · 2024Article
- A Multi-Scale-Enhanced YOLO-V5 Model for Detecting Small Objects in Remote Sensing Image Information.Sensors (Basel, Switzerland) · 2024Article
- Comprehensive Investigation of Unmanned Aerial Vehicles (UAVs): An In-Depth Analysis of Avionics Systems.Sensors (Basel, Switzerland) · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Object detection, as a fundamental task in computer vision, has been developed enormously, but is still challenging work, especially for Unmanned Aerial Vehicle (UAV) perspective due to small scale of the target. In this study, the authors develop a special detection method for small objects in UAV perspective. Based on YOLOv3, the Resblock in darknet is first optimized by concatenating two ResNet units that have the same width and height. Then, the entire darknet structure is improved by increasing convolution operation at an early layer to enrich spatial information. Both these two optimizations can enlarge the receptive filed. Furthermore, UAV-viewed dataset is collected to UAV perspective or small object detection. An optimized training method is also proposed based on collected UAV-viewed dataset. The experimental results on public dataset and our collected UAV-viewed dataset show distinct performance improvement on small object detection with keeping the same level performance on normal dataset, which means our proposed method adapts to different kinds of conditions.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.