Abstract: Referring remote sensing image segmentation (RRSIS) task aims to generate segmentation masks for target objects based on language descriptions. It requires precise localization while ...

This repository provides an end-to-end pipeline for medical image segmentation using deep learning. Implemented in Python with TensorFlow, OpenCV, and other popular libraries, this project includes ...

LLM-assisted manuscripts exhibit more complexity of the written word but are lower in research quality, according to a Policy Article by Keigo Kusumegi, Paul Ginsparg, and colleagues that sought to ...

Abstract: Domain Adaptation (DA) is important for a segmentation model to deal with domain shift in a new target domain. Due to the privacy concern of medical data and the expensive annotation process ...

With 4 million app downloads, Estonia-based startup Vocal Image aims to help people improve their voice and communication skills with AI-powered coaching. But out of its 160,000 active users, it may ...

As shown below, the inferred masks predicted by our segmentation model trained on the PNG dataset appear similar to the ground truth masks. If you would like to train ...

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 ...

Some critics speculate whether AI tools will replace human designers, but I believe the reality is that generative AI is a new creative sidekick—an assistant that accelerates tedious tasks and unlocks ...

ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...

The MHSAttResDU-Net incorporates RCC for complexity control and improved generalization under varying lighting. The SSRP unit in encoder-decoder blocks reduces feature map dimensions, capturing key ...