Abstract: Developing deep learning models for accurate segmentation of biomedical CT images is challenging due to their complex structures, anatomy variations, noise, and unavailability of sufficient ...

Most data teams discover quality problems the same way: a dashboard looks wrong, a stakeholder files a ticket, and an engineer traces the damage backward through the pipeline. By then, the bad data ...

Could pure AI encoding reinvent compression and make traditional codecs obsolete? Monica Heck examines what the future might ...

Meta’s Brain2Qwerty v2 offers a breakthrough non-invasive brain-to-text AI model with 61% word accuracy, challenging ...

Abstract: While the encoder–decoder structure is widely used in the recent neural construction methods for learning to solve vehicle routing problems (VRPs), they are less effective in searching ...

A glass of water may look perfectly uniform, but at the molecular level, it could be carrying two different forms that are ...

This tutorial shows how to use Keras library to build deep neural network for ultrasound image nerve segmentation. More info on this Kaggle competition can be found ...

In this work, we propose an unsupervised deep learning model to address multi-focus image fusion problem. First, we train an encoder-decoder architecture in unsupervised manner to acquire deep feature ...

A new 3D image projection system from researchers at the UCLA Samueli School of Engineering and the California NanoSystems Institute (CNSI) marks a major step toward overcoming a longstanding problem ...

Forensic science plays a vital role in identifying, characterizing, and quantifying physical and biological traces recovered from crime scenes — a task that ...