Over the past decade, advancements in machine learning (ML) and deep learning (DL) have revolutionized segmentation accuracy.

Artificial intelligence is accelerating material discovery and design by automating analysis, guiding experiments, and enabling predictive modeling across spectroscopy, microscopy, and synthesis.

A research team has developed a deep learning–driven computed tomography (CT) imaging pipeline that enables precise, ...

Deepfakes use two main algorithms: the generator and the discriminator. The generator is responsible for producing initial digital content by shaping training data based on the expected output, while ...

Computational optics integrates optical hardware and algorithms, enhancing imaging capabilities through joint optimization ...

This innovation allows the model to synthesize images without changing the hardware architecture; it merely needs to reconstruct the diffraction decoder ... deep learning. The core idea of the optical ...

Formula 1 has always been a showcase for engineering brilliance on track. In recent years, the same spirit has reshaped how ...

In the Age of AI, many health care providers dream of a digital assistant, unencumbered by fatigue, workload, burnout or ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...