Aim To implement a deep learning-based segmentation algorithm to quantify reticular pseudodrusen (RPD) and drusen volumes on optical coherence tomography (OCT) and investigate their association with ...

New research from FIU shows that some visual-language AI models have become particularly susceptible to image-based hacks.

It may look like a picture of a panda bear to you, but to your business's AI agent, it can act like a skeleton key, bypassing ...

Training a computer vision model on a 50:50 blend of synthetic and real eye images produces more reliable segmentation of the ...

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...

If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...

Image thresholding is one of the fastest and easiest approach for image segmentation and serves as a preprocessing step in computer vision and image processing applications, such as surveillance, ...

Brain tumors account for roughly one in four cancer-related deaths. The task of brain tumor segmentation is particularly challenging, as different tumor types require distinct segmentation approaches.

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 ...

Computer vision powers machines' ability to understand visual information - from basic image recognition to complex scene interpretation. Instance segmentation takes this capability further, enabling ...