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 ...

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.

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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 ...

This review focuses on the recent advancements in neuroimaging enabled by deep learning techniques, specifically highlighting their applications in brain disorder detection and diagnosis. The ...

AxSTREAM AI can accelerate engineering decisions with workflow-aware intelligence. Read on for a brief market rundown and a few expert takes on how materials innovations are taking shape in 2026 and ...