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17 wrz 2023 · In this paper, we propose a novel method called Frustum 3DNet (F-3DNet) for 3D object detection from point clouds in IoT. Our approach utilizes the inner order of point clouds to construct a rearranged feature matrix and generate a pseudo panorama from LiDAR data.
The 3DNet dataset is a free resource for object class recognition and 6DOF pose estimation from point cloud data. 3DNet provides a large-scale hierarchical CAD-model databases with increasing numbers of classes and difficulty with 10, 60 and 200 object classes together with evaluation datasets that contain thousands of scenes captured with an ...
Ansys Discovery features the first simulation-driven design tool combining instant physics simulation, high-fidelity simulation and interactive geometry modeling in a single easy-to-use experience. Ansys Discovery Reveals Critical Insights Early in the Design Process.
1. About Ansys Discovery. 1.1. Installation and Licensing Considerations; 1.2. Quality Assurance Services; 1.3. Functional Differences Between Simulation Stages. 1.3.1. Structural Physics; 1.3.2. Fluid Flow Physics; 1.3.3. Solid Thermal Physics; 1.3.4. Physics Combinations and Calculation Types; 1.3.5. Fidelity Control; 1.3.6. Optimization ...
17 wrz 2023 · In this paper, we propose a novel method called Frustum 3DNet (F-3DNet) for 3D object detection from point clouds in IoT. Our approach utilizes the inner order of point clouds to construct a...
18 wrz 2023 · In this paper, we propose a novel method called Frustum 3DNet (F-3DNet) for 3D object detection from point clouds in IoT. Our approach utilizes the inner order of point clouds to construct a rearranged feature matrix and generate a pseudo panorama from LiDAR data.
1 maj 2012 · To overcome the training issue, we introduce a methodology for learning 3D descriptors from synthetic CAD-models and classification of never-before-seen objects at the first glance, where...
