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 ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...

These 2026 fantasy baseball deep breakout infielders are undervalued draft targets who can return massive value in the late rounds and deeper formats. Pittsburgh Pirates shortstop Konnor Griffin who ...

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 ...

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 ...

In marine ecology research, it is crucial to accurately identify the marine mammal species active in the target area during the current season, which helps researchers understand the behavioral ...

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 ...

Abstract: Large-scale, high-quality data are considered an essential factor for the successful application of many deep learning techniques. Meanwhile, numerous real-world deep learning tasks still ...

Data-driven methods have been revolutionizing the way physicists and engineers handle complex and challenging problems even when the physics is not fully understood. However, these models very often ...