As AI models move from design to production, mining engineers face a double-faceted challenge: delivering real-time performance on embedded devices with ...

Abstract: Single-shot fringe projection profilometry (FPP) is crucial for real-time or dynamic 3-D measurement scenarios. In this regard, we propose a spatial composite FPP (SCFPP), which creatively ...

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 ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

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 ongoing revolution in deep learning is reshaping research across many fields, including economics. Its effects are especially clear in solving dynamic economic models. These models often lack ...

Who knew there were so many categories of cleaning? There's deep cleans, spring cleans, maintenance cleans, garage/attic/basement clean outs — the list really does go on and on. However, two of the ...

El Niño-Southern Oscillation (ENSO) is the strongest interannual variability signal in Earth's climate system. The shifts between its warm and cold phases profoundly impact global extreme weather, ...

Abstract: In this paper, an approach based on projection neural network (PNN), sliding mode control technique, and deep learning is proposed to solve the energy management problem of multi-energy ...

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 ...

This Collection calls for submissions of original research into techniques that facilitate the advancement of deep learning for image analysis and object detection, driving computer vision forward and ...