Fast Deep Vehicle Detection in Aerial Images

Sommer, Lars Wilko, Schuchert, Tobias, Beyerer, Jurgen·2017·2017 IEEE Winter Conference on Applications of Computer Vision (WACV)

Cited by (138)

Items 101–138 of 138

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  18. A Novel Self-Adaptive Vehicle Segmentation Method in Traffic Video with Symmetric Frame Difference Constraints
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  24. Selective Deep Convolutional Framework for Vehicle Detection in Aerial Imagery
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  25. Vessel Detection Based on Deep Learning Approach
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  28. Efficient Lightweight UAV Image Target Detection Model Based on YOLOv7
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  29. Benchmarking SRGAN-Upscaled YOLO for Enhanced Object Detection in Aerial Imagery
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  30. Réseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne
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  31. Classification de données massives de télédétection
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  32. Real-Time Vehicle Monitoring: A Unified Framework for Detection, Tracking, and Behavioural Classification
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  33. Object detection method based on aerial image instance segmentation received by unmanned aerial vehicles in the conditions rough for visualization
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  34. SFC-YOLO: An Accuracy-Enhanced and Parameter-Efficient YOLO Framework for Small Vehicle Detection in Aerial Images
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  35. DCPNet: Enhancing small object detection in remote sensing with Dual-Stream complementary perception
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  37. Learning a Rotation Invariant Detector with Rotatable Bounding Box
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  38. Perceiving traffic from aerial images
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