Deep learning has transformed remote sensing, driving state-of-the-art results in land use and land cover classification, ...

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.

A three-stage pipeline progressed from slit-lamp image training to smartphone optimization and public self-capture, incorporating human-computer interface refinements and preprocessing to improve real ...

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

Abstract: Deep learning (DL) has become a central approach for ship classification using synthetic aperture radar (SAR) imagery. This survey reviews 74 representative studies selected from 187 ...

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 ...

Analytical technology was applied in the field of cultural heritage science in the 1980s 4,5,6. Since then, rapid technological development has inspired numerous studies that have primarily explored ...

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...

The era of A.I. propaganda is here — and President Trump is an enthusiastic participant. After nationwide protests this weekend against Mr. Trump’s administration, the president posted an ...

This repository contains Python notebooks demonstrating image classification using Azure AutoML for Images. These notebooks provide practical examples of building computer vision models for various ...