withoutBG is a high-quality background removal tool. They built their open-source image matting and refiner models using smp.Unet and are proudly sponsoring this project.

Learn how Intersection over Union (IoU) works and how to implement it step-by-step using PyTorch. This guide covers everything from the basic concept to practical coding examples for object detection ...

To automate bone marrow segmentation within pelvic bones in quantitative fat MRI of myelofibrosis (MF) patients using deep-learning (DL) U-Net models. Automated segmentation of bone marrow (BM) was ...

Abstract: U-Nets have been established as a standard neural network architecture for image-to-image problems such as segmentation and inverse problems in imaging. For high-dimensional applications, as ...

This repo contains a PyTorch an implementation of different semantic segmentation models for different datasets. Note that when using COCO dataset, 164k version is used per default, if 10k is prefered ...

Deep convolutional neural network (CNN) greatly promotes the automatic segmentation of medical images. However, due to the inherent properties of convolution operations, CNN usually cannot establish ...

The basic principles required to solve classification tasks with neural networks are used as building blocks in more complicated deep learning problems such as object detection and instance ...

Cells were stained by tartrate-resistant acid phosphatase (TRAP) staining (Sigma-Aldrich, St. Louis, MO, United States), and images were captured using the BZ-X810 inverted microscope (Keyence, Osaka, ...

Image segmentation is crucial for various Computer Vision tasks, aiding in image classification and object detection. Segmentation techniques can be categorised into semantic, instance, and panoptic ...