Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...

Abstract: Deep learning for classifying brain tumors has transformed medical image analysis, significantly improving upon manual detection techniques. Brain tumors are defined by aberrant cellular ...

This group project explores the use of neural networks to model avalanche hazard forecasts using a 15-year dataset from the Scottish Avalanche Information Service (SAIS). Our group has been assigned ...

Background: With optical coherence tomography (OCT), doctors are able to see cross-sections of the retinal layers and diagnose retinal diseases. Computer-aided diagnosis algorithms such as ...

Abstract: Impacted molars, which fail to erupt properly, represent a common dental pathology often causing pain and complications. Panoramic radiography remains the primary diagnostic tool, but its ...

Trained a deep learning-based system using high-resolution Sentinel-2 imagery and CNNs to classify land into water, vegetation, urban and barren areas with 92.4% validation accuracy.

Gemini’s mobile adoption has been soaring since the August launch of its Nano Banana image editor model, which has received positive reviews, particularly from users who say they can now more easily ...