[Retracted] U‐Net‐Based Medical Image Segmentation
Deep learning has been extensively applied to segmentation in medical imaging. U‐Net
proposed in 2015 shows the advantages of accurate segmentation of small targets and its …
proposed in 2015 shows the advantages of accurate segmentation of small targets and its …
Automatic sleep staging of EEG signals: recent development, challenges, and future directions
H Phan, K Mikkelsen - Physiological Measurement, 2022 - iopscience.iop.org
Modern deep learning holds a great potential to transform clinical studies of human sleep.
Teaching a machine to carry out routine tasks would be a tremendous reduction in workload …
Teaching a machine to carry out routine tasks would be a tremendous reduction in workload …
Lgm: Large multi-view gaussian model for high-resolution 3d content creation
Abstract 3D content creation has achieved significant progress in terms of both quality and
speed. Although current feed-forward models can produce 3D objects in seconds, their …
speed. Although current feed-forward models can produce 3D objects in seconds, their …
Anydoor: Zero-shot object-level image customization
This work presents AnyDoor a diffusion-based image generator with the power to teleport
target objects to new scenes at user-specified locations with desired shapes. Instead of …
target objects to new scenes at user-specified locations with desired shapes. Instead of …
UIU-Net: U-Net in U-Net for infrared small object detection
Learning-based infrared small object detection methods currently rely heavily on the
classification backbone network. This tends to result in tiny object loss and feature …
classification backbone network. This tends to result in tiny object loss and feature …
Omniobject3d: Large-vocabulary 3d object dataset for realistic perception, reconstruction and generation
Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of
large-scale real-scanned 3D databases. To facilitate the development of 3D perception …
large-scale real-scanned 3D databases. To facilitate the development of 3D perception …
Texture: Text-guided texturing of 3d shapes
In this paper, we present TEXTure, a novel method for text-guided generation, editing, and
transfer of textures for 3D shapes. Leveraging a pretrained depth-to-image diffusion model …
transfer of textures for 3D shapes. Leveraging a pretrained depth-to-image diffusion model …
Mvimgnet: A large-scale dataset of multi-view images
Being data-driven is one of the most iconic properties of deep learning algorithms. The birth
of ImageNet drives a remarkable trend of" learning from large-scale data" in computer vision …
of ImageNet drives a remarkable trend of" learning from large-scale data" in computer vision …
Sketch-guided text-to-image diffusion models
Text-to-Image models have introduced a remarkable leap in the evolution of machine
learning, demonstrating high-quality synthesis of images from a given text-prompt. However …
learning, demonstrating high-quality synthesis of images from a given text-prompt. However …
Kubric: A scalable dataset generator
Data is the driving force of machine learning, with the amount and quality of training data
often being more important for the performance of a system than architecture and training …
often being more important for the performance of a system than architecture and training …