Abstract: This research addresses the challenge of camera calibration and distortion parameter prediction from a single image using deep learning models. The main contributions of this work are: (1) ...

Deep learning algorithms for ultra-widefield fundus photos can identify retinal detachments with precision, supporting early diagnoses in varied settings. Deep learning (DL) models applied to ...

Abstract: Flood mapping using remote sensing data is critical to disaster response, especially in real-time monitoring and edge deployment. However, existing deep-learning (DL) models often face ...

Finland has spent decades digging caves into its bedrock. Now, as Russia rears its head, nervous Finns want to know: “Where’s my shelter?” Credit... Supported by By Sally McGrane Visuals by Vesa ...

Learn about DenseNet, one of the most powerful deep learning architectures, in this beginner-friendly tutorial. Understand its structure, advantages, and how it’s used in real-world AI applications.

Nothing dominates the technology news cycle more than AI in its many forms, and for data professionals, the discussion often mentions deep learning. But what are the use cases for this technology? How ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...

This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. It demonstrates how to use MATLAB® and Simulink® for data preparation and ...

A few years back, one of us sat in a school district meeting where administrators and educators talked about the latest student achievement results. The news was not good. Students’ test scores hadn’t ...