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Found 3 papers, 2 papers with code
Object Semantics Give Us the Depth We Need: Multi-task Approach to Aerial Depth Completion
Depth completion and object detection are two crucial tasks often used for aerial 3D mapping, path planning, and collision avoidance of Uncrewed Aerial Vehicles (UAVs).
Single-stage uav detection and classification with yolov5: Mosaic data augmentation and panet
In Drone-vs-Bird Detection Challenge in conjunction with the 4th International Workshop on Small-Drone Surveillance, Detection and Counteraction Techniques at IEEE AVSS 2021, we proposed a YOLOV5-based object detection model for small UAV detection and classification.
A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated Learning
We trained a BERT-based NER model with WikiPII and showed that with an adequately large training dataset, the model can significantly decrease the cost of manual information extraction, despite the high level of label noise.
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