a, Comparison of 2D holograms synthesized using several different wave propagation models, including free-space propagation, a physically motivated model and our proposed model combining physics and learnable parameters that are calibrated using camera feedback.b, Comparison of two 3D holograms. Zoomed-i...
NGG retrieves genetic markers in epistatic signals improving machine learning procedures.AAnalysis scheme employed to measure the effect of the 2D GWAS signal to improve phenotypic predictions. The dataset is divided into a train set (50%) and a test set (50%). The train set is used to perf...
Swin-Unet [29] is a pure Transformer network structure, where the encoder and decoders are composed of Transformers. However, Swin-Unet is a model for 2D medical image segmentation, which is not applicable to voxel segmentation of 3D medical images unless a lot of additional work has been ...
The camera's height, azimuth, and inclination were recorded to establish a reference frame fixed to the ground. Two-dimensional projection of 3D trajectory data To conduct a comparative analysis between 3D and 2D trajectories, two methods were employed to convert the 3D dataset to a 2D one. 1...
Structure from motion (SfM)This technique can estimate 3D models from sequences of overlapping 2D images and can automatically recover the camera parameters like focal length, distortion, position and orientation [91,92,93,94]. It has low-cost, high point cloud accuracy, and high color reproduct...
pretrained_model_name_or_path: './ckpts' # pretrained_unet_path: './ckpts' pretrained_model_name_or_path: 'flamehaze1115/wonder3d-v1.0' # or './ckpts' revision: null validation_dataset: root_dir: "./example_images" # the folder path stores testing images @@ -23,7 +22,7 @@ ...
Although Cellpose uses 2D data for training, the algorithm can be extended for 3D segmentation prediction by slicing a volume dataset into 2D images according to XY, XZ an YZ orientations that are recombined into 3D. In recent works, the freely available generalist Cellpose algorithm was mainly ...
Due to the commonly-existing limitations of deep CNN-based segmentation in sliding-windowed dense pixel label prediction, such as limited receptive filed, high memory burden and computation complexity, full CNNs (FCNNs), including 2D and 3D FCNNs serve as the backbone in many volumetric image se...
proposed the si descriptor, which was one of the earliest 3d local feature descriptors. this descriptor defines the normal of the local surface as a reference axis and spins a 2d plane around the axis, which is then divided into several bins. the number of points falling in each bin is ...
3D objects, approximating any given shape as a finite collection of interconnected 2D polygons and vertices. As the number of polygons increases, the accuracy of the approximation improves, however the rendering time of the mesh increases accordingly. While render times are important in any 3D ...