In an era where cloud-native architectures are at the forefront of digital transformation, regulatory compliance has become ...

The integration of deep learning in neuroimaging enhances diagnostic capabilities, offering new insights into neurological ...

At the core of AI’s value in cancer care is its performance in early detection and diagnostic support, where deep learning ...

On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet, the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 ...

From predictive analytics to autonomous control, AI is making renewable energy systems smarter, faster, and more efficient.

Radiologists who evaluate CT scans have diagnostic challenges due to the complexity of underlying anatomy and the potential ...

When visual information enters the brain, it travels through two pathways that process different aspects of the input. For ...

Beyond detection, the platform employs a large language model, specifically GPT-3.5, to recommend context-specific remediation strategies. Upon identifying vulnerable packets, the CyBERT model passes ...

Simulations showed that by using the BGG model, it is possible to alter network dynamics from a vulnerable 4/7 corrupted node ratio to a safer 4/9 distribution through the timely release of backup ...

A recent study introduces an advanced anomaly-based intrusion detection system (IDS) designed to address the increasing cyber threats targeting Internet of Things (IoT) devices. By combining machine ...