Here are 11 free NPTEL data science and analytics courses from leading IITs cover graph theory, Bayesian modelling, Python, R ...

There is lots of talk of AI skills, but what actually are they? Digging into new research, Dan Fitzpatrick explores the ...

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN integration. It improves dynamic lesion detection, temporal ...

Abstract: We propose a variational Bayesian (VB) implementation of block-sparse Bayesian learning (BSBL) to compute proxy probability density functions (PDFs) that approximate the posterior PDFs of ...

Abstract: The objective of optical super-resolution (SR) imaging is to acquire reliable sub-diffraction information on bioprocesses to facilitate scientific discovery. Structured illumination ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

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Experimental variogram modelling is an essential process in geostatistics. The use of artificial intelligence (AI) is a new and advanced way of automating experimental variogram modelling. One part of ...

Abstract: To overcome the effect of grid mismatch on the superresolution performance, a sparse Bayesian learning-based multichannel radar forward-looking superresolution imaging scheme is proposed in ...

The sinking of tech billionaire Mike Lynch’s yacht in a freak storm off the Sicilian coast last week certainly has to rank among the most bizarre fatal celebrity accidents in years. There was the ...