A research team has developed a powerful unsupervised deep learning network that can accurately separate wood and leaf ...

Abstract: Medical image segmentation plays a crucial role in computer-aided diagnosis and treatment planning. Unsupervised segmentation methods that can effectively leverage unlabeled data bring ...

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...

1 College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China 2 Institute for Complexity Science, Henan University of Technology, Zhengzhou, China Tongue is ...

This important work presents a self-supervised method for the segmentation of 3D cells in fluorescent microscopy images, conveniently packaged as a Napari plugin and tested on an annotated dataset.

AI tools for image segmentation require large training datasets that are annotated with many examples of objects of interest, e.g. manual annotated cell nuclei for training a model for nuclear ...

Abstract: Unsupervised domain adaptation (UDA) for remote sensing image semantic segmentation aims to train a deep model on the labeled source domain and apply it to the unlabeled target domain.

Microsoft Deployment Toolkit is designed to streamline the deployment of Windows operating systems, applications, and configurations across multiple devices. If you want to capture Windows Image using ...