Abstract: In this paper, the cross-layer optimization problem of access point selection (APS) and beamforming (BF) in cell-free network (CFN) with local CSI is studied, where constraints of per AP ...
Abstract: Vehicle detection is vital for urban planning and traffic management. Optical remote sensing imagery, known for its high resolution and extensive coverage, is ideal for this task.
Abstract: A large number of collaborative manufacturing tasks are directly performed on point clouds. With the growing size of point clouds, the computational demands of these tasks also increase. One ...
Learn how to transform your photos into stunning 3D floating objects using a hidden Apple feature on your iPhone. This step-by-step tutorial shows you how to create eye-catching effects that bring ...
Abstract: The research on point-supervised oriented object detection has attracted more attention due to its convenience in annotation, as only point labels are required instead of full oriented ...
Abstract: Detection of small or distant objects is a major challenge in 3-D object detection in autonomous driving either through RGB images or LiDAR point clouds. Despite the growing popularity of ...
Abstract: Over the past few years, there has been remarkable progress in research on 3D point clouds and their use in autonomous driving scenarios has become widespread. However, deep learning methods ...
Abstract: Weakly textured objects are frequently manipulated by industrial and domestic robots, and the most common two types are transparent and reflective objects; however, their unique visual ...
Abstract: Oriented object detection in aerial images has made significant advancements propelled by well-developed detection frameworks and diverse representation approaches to oriented bounding boxes ...
Abstract: Aiming at the problem of poor edge effect segmentation in point cloud segmentation, which fails to fully utilize the correlation between the local geometric and semantic features of point ...
Abstract: At present, with the original point cloud as input, most of the object detectors use Pointnet++ to extract features of the point cloud based on the Farthest Point Sampling (FPS). However, ...
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