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 ...

Lithology identification is crucial for characterizing complex unconventional reservoirs, where thin interlayers significantly influence hydrocarbon accumulation. Although deep learning-based methods ...

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 ...

The Trump administration has expanded Palantir’s work with the government, spreading the company’s technology — which could easily merge data on Americans — throughout agencies. Alex Karp, a ...

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 ...

Welcome to the official repository of my internship journey with PalSoft for AI & Technology Solutions, where I successfully completed the training program titled: "Introduction to Deep Learning with ...

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 ...