Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn hidden patterns from various types of data, be it images, audio or text, to ...

To implement the National Institute of Health’s (NIH) requirement that funding recipients (a) provide training to all Senior/Key Personnel on Other Support disclosure obligations and (b) maintain a ...

ABSTRACT: Support vector regression (SVR) and computational fluid dynamics (CFD) techniques are applied to predict the performance of an automotive torque converter in the design process of turbine ...

Google announced a new multi-vector retrieval algorithm called MUVERA that speeds up retrieval and ranking, and improves accuracy. The algorithm can be used for search, recommender systems (like ...

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...

The task of training deep neural networks, especially those with billions of parameters, is inherently resource-intensive. One persistent issue is the mismatch between computation and communication ...

A new data creation paradigm and algorithmic breakthrough from Georgia Tech has laid the groundwork for humanoid assistive robots to help with laundry, dishwashing, and other household chores. The ...