Studies leveraging NIR and CNNs report accuracies exceeding 95%, with some achieving perfect classification for pure fibers.

A neuroscience breakthrough has been achieved using AI to identify neuron cell types from the brain activity recordings of ...

Image Classification,K-nearest Neighbor,Large Datasets,Learning Algorithms,Machine Learning,Machine Learning Classification Algorithms,Model Performance,Neural Network,Pre-trained Neural ...

A team of researchers at Rice University and Baylor College of Medicine has developed a new strategy for identifying ...

A new system that combines Gemini’s coding abilities with an evolutionary approach improves datacenter scheduling and chip ...

Computational psychiatry is an interdisciplinary field of research that applies computational methods to the early detection ...

When I first started working with integral field spectroscopic (IFU) data, I was struck by how much complexity was being ...

CAST, groups fine details into object-level concepts as attention moves from lower to high layers, outputting a ...

Reconfigurable datacenter networks (RDCNs), which can adapt their topology dynamically, based on innovative optical switching ...

A research team from Kumamoto University has developed a promising deep learning model that significantly enhances the ...

Across various classes, the researchers identified a model that, when coupled with appropriate data augmentation and ...

This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, version, scale, and secure your production machine learning 🚀 You can keep up to date by ...