7 Best ChatGPT Image Prompts in 2026: How to Get Better AI Photos

Use these prompt templates to generate sharper ChatGPT images in 2026, from hero sections and product shots to retouching and ...
Communications of the ACM

Where Are the City Trees? Monitoring Urban Trees across the U.S. Using Generative AI

Urban trees are critically important to mitigate poor air quality, excessive heat islands, and unmoderated rainwater overflow ...
Scientific Research Publishing

H-UQ-MFF: Hybrid Uncertainty-Aware Multi-Feature Fusion for Clinically-Translatable Glaucoma Detection with FDA-Compliant Validation ()

Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a ...
IEEE

A Deep Learning Multimodal Fusion-Based Method for Cell and Nucleus Segmentation

Abstract: In recent years, deep learning has been widely utilized in the fields of biomedical image segmentation and cellular image analysis. Supervised deep neural networks trained on annotated data ...
IEEE

EICSeg: Universal Medical Image Segmentation via Explicit In-Context Learning

Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
GitHub

What is Deep Learning?

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...
GitHub

4D- LATTE : 4D Radar Drivable Area Automatic Labelling Tools using Deep Learning

First 4D Radar Automatic Labelling tools using Segment Anything (SA) drivable area segmentation on camera using Deep Learning for Autonomous Vehicle. KAIST-Radar (K-Radar) (provided by 'AVELab') is a ...
Frontiers

Traditional machine learning in biomedical image analysis: before you go too deep

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...
EurekAlert!

Boundary-aware semi-supervised segmentation boosts 3D medical image accuracy

A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...
Scientific Research Publishing

From U-Net to Swin-Unet Transformers: The Next-Generation Advances in Brain Tumor Segmentation with Deep Learning ()

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...