AI enables a who's who of brown bears in Alaska

A team of scientists from EPFL and Alaska Pacific University has developed an AI program that can recognize individual bears ...
Communications of the ACM

Building Intelligent Agents with Neuro-Symbolic Concepts

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...
Proceedings of the National Academy of Sciences (PNAS)

Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
IEEE

Hybrid Deep Machine Learning Feature Selection for High-Dimensional Cybersecurity Data

Abstract: The rapid increase in cyber threats has heightened the demand for Intrusion Detection Systems (IDS) that are both accurate and efficient. While deep learning models outperform traditional ...

LLMs can identify major depressive disorder via voice note recordings

A new medical large language model (LLM) achieved over 91% accuracy in identifying female participants diagnosed with major ...
EurekAlert!

Medical LLMs may show real-world potential in identifying individuals with major depressive disorder using WhatsApp voice note recordings

A new medical large language model (LLM) achieved over 91 percent accuracy in identifying female participants diagnosed with major depressive disorder after analyzing a short WhatsApp audio recording ...
IEEE

Towards Optimised SORT Tracking Algorithm: Tuning the Feature Extractor Base-Model

Abstract: Multi-object tracking (MOT) is essential in applications such as surveillance, security, healthcare, and autonomous driving, where effective feature extraction is critical to the performance ...