Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...
Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...
UQLM provides a suite of response-level scorers for quantifying the uncertainty of Large Language Model (LLM) outputs. Each scorer returns a confidence score between 0 and 1, where higher scores ...
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Abstract: The increasing reliance on GPS systems in Unmanned Aerial Vehicles (UAVs) has made the need for an efficient and robust system to detect, mitigate, and prevent potential disruption during ...
In this work, we identify two key observations about spatiotemporal redundancy in videos: Temporal redundancy is not bound to fixed spatial locations. Semantically consistent elements in videos often ...
Abstract: Cyberattacks pose a significant threat to internet security and may cause great damage to businesses. Machine learning methodologies have been widely used to detect cyber intrusions. This ...
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