Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

Veritas.AI is designed to advance the functionality of Spectrum Dynamics’ VERITON-CT scanner for nuclear imaging.

Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

FAYETTEVILLE, GA, UNITED STATES, January 29, 2026 /EINPresswire.com/ -- Accurate atmospheric temperature profiles are ...

Recent research (2024-2025) consistently demonstrates the advantages of integrated AI-VR training: Knowledge Acquisition: ...

During his more than two decades with Nvidia, Rev Lebaredian has had a ringside seat to the show that has been the evolution of modern AI, from the ...

But this breakthrough doesn't stand alone; recent developments in plastic science and recycling include pyrolysis research to ...

Artificial Intelligence (AI) is revolutionizing the dynamics of technological advancement in the field of medical imaging, ...