The Pentagon has demanded unrestricted AI models from OpenAI, Google, and xAI for classified military networks, but Anthropic has refused over weapons concerns.
Abstract: The UC Merced (UCM) land use dataset is a widely adopted benchmark for evaluating aerial image classification algorithms. This paper presents a comparative performance analysis of prominent ...
High school students gain PhD-led mentorship, publish original research, and build real-world AI models through ...
A recent review concluded that artificial intelligence (AI) is rapidly transforming the diagnosis and treatment of haematological malignancies by enhancing diagnostic accuracy and ...
The Pentagon pushes AI companies like OpenAI and Anthropic to deploy tools on both classified and unclassified networks amid ongoing debates.
Deep Learning-Based Models for Paddy Disease Classification and Segmentation: An Experimental Review
Abstract: Early-stage diagnosis of paddy diseases, based on initial visible symptoms, is crucial for minimizing chemical use and preventing the spread of disease. Automated paddy disease diagnosis can ...
The rapid emergence of Large Language Models (LLMs) and generative AI is reshaping how people and organizations access, synthesize, and apply knowledge.
Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
Mass General Brigham researchers are betting that the next big leap in brain medicine will come from teaching artificial ...
Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...
Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
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