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 ...

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 ...

Google has announced new features in the popular Google Finance platform, and it leans heavily on Google’s tried-and-true strategy of more AI in more places. This builds on Google’s last Finance ...

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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 ...

This study aimed to develop a hybrid deep learning model for classifying multiple fundus diseases using ultra-widefield (UWF) images, thereby improving diagnostic efficiency and accuracy while ...

Climate change has significantly impacted vulnerable communities globally, with rising temperatures caused by greenhouse gas emissions accelerating global Sea Level Rise (SLR), threatening coastal ...

Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...