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 ...

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data/ ├── noise/ # Background noise samples used for mixing ├── train/ # Training dataset │ ├── clean_trainset_wav/ # Clean training audio │ └── noisy_trainset_wav/ # Noisy training audio ├── validate ...

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 ...

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 ...

Extreme weather events such as heatwaves, cyclones, floods, wildfires, and droughts are becoming more frequent due to climate change. Climate change causes shifts in biodiversity and impacts ...

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: We introduce a novel structure empowered by deep learning models, accompanied by a thorough training methodology, for enhancing channel estimation and data detection in multiple input ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

Objective: This study aims to develop a multimodal deep learning-based stress detection method (MMFD-SD) using intermittently collected physiological signals from wearable devices, including ...