Researchers from Nanyang Technological University, Wuhan University, and ByteDance have proposed a novel paradigm Text4Seg++, ...

Abstract: Combining convolutional neural networks (CNNs) and transformers is a crucial direction in remote sensing image semantic segmentation. However, due to differences in the spatial information ...

Image preprocessing is the first step in OCR technology, aimed at improving image quality to create favorable conditions for subsequent character recognition. Vehicle document images may be affected ...

A product photo on Shein briefly appeared to show the likeness of Luigi Mangione, the 26-year-old accused of murdering ...

This repository contains the code implementation for the paper RSRefSeg: Referring Remote Sensing Image Segmentation with Foundation Models, developed based on the MMSegmentation project. The current ...

Medical image segmentation is one of the most important tasks in modern healthcare. Every pixel in a scan tells a story, whether it marks a healthy cell, a cancerous growth, or a vital organ boundary.

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.

This repository contains the official implementation of "MedVisionLlama: Leveraging Pre-Trained Large Language Model Layers to Enhance Medical Image Segmentation" by Gurucharan Marthi Krishna Kumar, ...