Knowing the exact depth of object in 3D cameras is critical to avoid drones and robots crashes. In this project I'm training Conventional, Unet and GAN autoencoder networks on depth and infra red ...

We provide DeepMedic and 3D UNet in pytorch for brain tumore segmentation. ... -rendering 3d-detection feature-pyramid-network self-supervised-learning 3d-unet multi-view region-proposal-network ...

Because 2D images are highly distinguishable, constructing a 3D model from multiple 2D views is one of the most common methods of 3D model retrieval. Normalization is typically challenging and ...

242504 Introduction: Delineating tumors in PET/CT images involves manual segmentation, which is both time-consuming and error-prone due to variability between observers. To address this, we trained a ...

In order to adapt compression to the structural characteristic of plenoptic image, in this paper, we propose a Data Structure Adaptive 3D-convolutional(DSA-3D) autoencoder. The DSA-3D autoencoder ...