Abstract: Target tracking in the maritime domain is a challenging problem due to several factors such as fluctuating and spiky sea clutter that is non-Gaussian with low target signal-to-interference ...

A 2017 Google paper introduced the transformer architecture, revolutionizing AI language processing. This innovation moved ...

Abstract: Most of the existing infrared and visible image fusion algorithms rely on hand-designed or simple convolution-based fusion strategies. However, these methods cannot explicitly model the ...

A novel machine learning algorithm retrieves remote sensing reflectance (Rrs) from Himawari 8 geostationary data at 10 minute ...

The main differences between the algorithms can be best understood via their respective compute_loss() functions. The NextLat training code includes inline comments to help explain the algorithm.

Endoscopy-based deep learning algorithms achieve higher sensitivity, specificity, and overall diagnostic accuracy than endoscopists for early ESCC detection.

Regardless of the cognitive and environmental concerns arising from humanity’s increasing use of AI which resulted recently in Pope Leo XIV ...

A tiny robot developed by Japan's space agency operated autonomously on the moon for more than 100 minutes and sent a series of images back to Earth. Exploring the moon’s surface lays crucial ...

Tracking 3D objects accurately and consistently is crucial for autonomous vehicles, enabling more reliable downstream tasks such as trajectory prediction and motion planning. Based on the substantial ...

Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...

On Wednesday, Jelani Nelson, a professor of theoretical computer science and chair of UC Berkeley's electrical engineering and computer science division, announced he was taking a leave of absence to ...